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Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Forest & Environment is the property of Journal of Forest & Environment Editorial and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The effect of cyflumetofen (CYF) on non-target organism earthworms (Eisenia fetida) in soil is unclear. In this study, a method was established for detection of CYF in earthworms. The samples were extracted with acetonitrile, the lipid in the earthworms was removed by liquid-liquid extraction, and then the concentration of CYF was detected by normal phase-HPLC. The results showed that the recoveries were 84%-88%, and the relative standard deviation was 1.3%-3.1% at the spiking levels of 0.5, 5, and 10 mg/kg, which verified the reliability of the method. According to the Biota-soil accumulation factor (BSAF), the enrichment concentration of the two enantiomers reached the maximum on the 7th day that the earthworms were enriched with CYF, and the enrichment ability of (+)-CYF in the earthworms was significantly higher than that of (−)-CYF. Long-term exposure of 0.5-10 mg/kg CYF for 28 days seriously inhibited the body weight of earthworms. The acute toxicity of cyflumetofen to earthworms was detected by filter paper method. The LC50 of rac-CYF, (−)-CYF, and (+)-CYF to earthworms was 162.5, 323.1 and 309.4 mg/L, respectively. According to the combined toxicity analysis, AI = −0.03 was obtained. The simultaneously use of the two enantiomers of CYF will cause additive toxicity to earthworms. [ABSTRACT FROM AUTHOR]

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food & Machinery is the property of Food & Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Forest Engineering is the property of Forest Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of South China Fisheries Science is the property of South China Fisheries Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An accurate runoff prediction is the prerequisite for the optimal allocation and efficient utilization of water resources, and the basis for making flood control and disaster reduction decisions. However, due to the influence of human activities, environment, climate and other actors, runoff series show nonlinear, unsteady and multi-scale changes, which increases the difficulty of accurate runoff prediction. In order to improve the accuracy and credibility of runoff prediction, this paper combines the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method. Quantum Particle Swarm Optimization (QPSO), Broad Learning System (BLS) model, a combined runoff prediction model based on CEEEDAN-QPSO-BLS is proposed. Firstly, CEEMDAN method is used to decompose the original runoff signal to obtain several relatively stationary intrinsic mode components. Secondly, the QPSO algorithm is used to optimize the number of node groups in the feature layer, the number of node groups in the enhancement layer and the number of nodes in the group of BLS model, and the optimal topology structure of the width learning network is obtained. Then, the optimal QPSO-BLS is used to predict multiple steady-state components, and the prediction components are reconstructed so as to obtain higher prediction accuracy. In this model, the daily runoff value of Xiaolangdi Reservoir in the Yellow River Basin is used as the experimental data, and EMD-QPSO-BLS and QPSO-BLS are used as the comparison model of CEEMDAN-QPSO-BLS. Nash-Sutcliffe efficiency coefficient (NSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Per centage Error (MAPE) are used to evaluate the reliability and accuracy of the model prediction. The experimental results show that, compared with QPSO-BLS with EMD-QPSO-BLS models, the prediction accuracy of CEEMDAN-QPSO-BLS is improved by 79.87% and 19.80%, and the credibility is improved by 131.2% and 10.98%, respectively. This paper provides decision-making support for flood control and drought relief to protect people s lives and property and sustainable development. [ABSTRACT FROM AUTHOR]

To improve the efficiency and accuracy of drug residue detection in agricultural products, this paper develops an automated sample preparation platform suitable for various sample matrices and preprocessing methods. The platform integrates functions such as oscillatory extraction, ultrasonic extraction, homogenization extraction, solid-phase extraction, liquid-liquid extraction, dispersive solid-phase extraction, nitrogen concentration, and calibration curve configuration. Simultaneously, it utilizes optimized salting modules, centrifuge-assisted positioning structures, and pendulum-type oscillation to achieve the automation of the sample preparation process. Experimental validation demonstrates that the system can efficiently process different samples, with average recovery rates for 22 pesticides and 12 veterinary drugs ranging from 75.4% to 115.0%, and relative standard deviations between 1.06% and 12.10%, meeting the requirements of GB/T 27404--2008. This automated sample preparation platform possesses broad applicability and has the potential to drive the automation of agricultural testing. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Refrigeration Technology is the property of Shanghai Society of Refrigeration and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: SSS (sea surface salinity) is an important physical and chemical indicator describing ocean state, and is also one of the most critical variables in global water cycle. In order to achieve largescale and continuous observation of the ocean salinity, SMOS (soil moisture and ocean salinity) mission is launched by European Space Agency to access brightness temperature for SSS retrieval. However, researches have pointed out that the accuracy of SMOS ocean salinity products cannot fully achieve scientific expect. Thus, a novel and effective method is desired for improving SMOS salinity. Methods: This paper selects study area in the Southeast Pacific, where the region is relatively less affected by radio frequency interference. The downloaded array for real-time geostrophic oceanography SSS data, SMOS level2 ocean salinity products and the Auxiliary data in the whole year of 2018 are matched both temporally and spatially. Based on the remote sensing mechanism and radiation transfer theory, five variables, including the first Stokes parameter (TH+TV), SST, UN10, VN10 and Ω are selected as sensitive factors. The ocean salinity retrieval model based on random forest is first established, and GridSearchCV(GS) algorithm is applied to optimize superparameters of the initial model, which is able to improve SSS accuracy further. Results: The experiment results show that： (1) For objective measurement, the mean absolute error (MAE) and root mean square error (RMSE) are adopted to compare the accuracy of the produced SSS from two established models and the SMOS products, in terms of Argo in-situ SSS as reference. According to experiments, MAEs of basic RF(random forest) model and GS‐RF model are both 0.08, which is evidently lower than SMOS SSS product's 0.66. Similarly, RMSEs of two models are also remarkable lower than SMOS's 0.93, while GS RF model is 0.14, indicating its slight advantage over RF model, which is 0.15. (2) All SSS retrieved from RF model and GS RF model distribute concentratedly around 36 psu, while SMOS ocean salinity product occasionally presents abnormal SSS that beyond 40 psu or below 30 psu, which is inappropriate. (3) In the testing set, error of SMOS SSS can reach −12.9 psu and 6 psu, while errors of two established models are no more than ±1.3 psu, noticeably lower than SMOS product. Meanwhile, GS‐RF model also present slight advantage than basic RF model on error measurement. Conclusions: Through experiments and analyses, we found that it is feasible to establish sea surface salinity retrieval methods based on random forest model, by deliberately selecting SSS sensitive factors, and advancedly optimizing super-parameters of model, especially with GridSearchCV algorithm. This paper has achieved reliable and satisfactory results, which have greatly improved the accuracy of ocean salinity data compared with SMOS products, thus benefit for relevant marine studies. [ABSTRACT FROM AUTHOR]

Copyright of China Surfactant Detergent & Cosmetics is the property of China Surfactant Detergent & Cosmetics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Natural Gas Industry is the property of Natural Gas Industry Journal Agency and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ecological Science is the property of Ecological Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Feed Research is the property of Editorial Board of Feed Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: In view of the low accuracy of flow forecast in tidal reach due to the combined influence of runoff and tide, combining the ability of variational mode decomposition (VMD) to process non-stationary signals and the advantages of back propagation (BP) neural network to deal with nonlinear problems, this paper proposes a new method for discharge prediction in tidal reach based on the combination model of tidal current harmonic analysis and VMD-BP neural network. Methods: First, the harmonic analysis method is used to separate the tidal discharge and residual discharge from the original discharge. Second, a BP neural network is constructed based on error backpropagation algorithm. Then, the BP neural network is used to simulate and train the power flow data and residual current data processed by VMD. Finally, the output tidal discharge and residual discharge components are superimposed and reconstructed to obtain the final discharge prediction results. Results: Experiments performed at the Xuliujing section of the Yangtze Estuary show that the discharge prediction accuracy of BP neural network method is better than that of traditional harmonic analysis method, with the root mean square error (RMSE) is decreased by about 3 400 m³ /s, and the relative standard accuracy (RSD) is increased by about 6%. In addition, compared with the traditional method, RMSE of the proposed method in this paper is decreased by about 5 000 m³ /s, and the RSD is increased by about 9%. Conclusions: The combined model based on harmonic analysis and VMD-BP neural network can effectively improve the prediction accuracy of discharge in tidal reach. At the same time, it also provides a new idea for the discharge prediction in the waters with variable flow conditions. [ABSTRACT FROM AUTHOR]

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanxi Agricultural Sciences is the property of Shanxi Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, the inactivation kinetics of potassium sorbate-assisted high pressure thermal sterilization (HPTS) on Bacillus subtilis spores were studied. First-order kinetics model, Weibull and Log-logistic kinetics models were used to fit the inactivation curve of B. subtilis spores by potassium sorbate-assisted HPTS. By analysis of precision factor (Df), bias factor (Bf), root mean square error (RMSE), coefficient of determination (R²), In the three models, Log- logistic Kinetic model fitted best the spore sterilization effect of potassium sorbate-assisted HPTS (R² =0.986). When potassium sorbate (0.2g/100mL) assisted HPTS (600 MPa, 75 25min), the inactivation effect was the best, and the spore inactivation was 6.10 lg (CFU/mL). Potassium sorbate assisted HPTS treatment was applied to the inactivation of spores in muskmelon juice, it was found that the browning degree was significantly reduced, after 28 days of storage, the absorbance of potassium sorbate (0.1g/100mL) assisted HPTS (600 MPa, 75 25 min) at 420 mn reached 0.093, The absorbance of the HPTS-treated control sample was 0.058. Scanning electron microscope was used to observe the microstructure of Bacillus subtilis spores in muskmelon juice before and after treatment, and it was found that the morphological structure of the spores changed after treatment. In conclusion, potassium sorbate assisted HPTS has significant application value. [ABSTRACT FROM AUTHOR]

Copyright of China Surfactant Detergent & Cosmetics is the property of China Surfactant Detergent & Cosmetics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem of due-date forecasting for make-to-order production environment, this paper proposed a forecasting method namely BDDF, which integrated multi-level workloads such as order accept, order release and workshop scheduling. This method first estimated the workload of "drum-chain" and "non-drum chain" orders at different levels according to whether the order passed through the bottleneck, and then estimated the throughput time of each level by using Little's law to sum and predict the due-date of the order. This paper used the FlexSim modeling and simulation to compare the system performance of BDDF method and two classical due-date prediction methods under different sequencing rules in the pre-shop, dispatching rules in the workshop, and protective capacity for the bottleneck. The results show that the BDDF method is superior to the classical methods in terms of mean tardy rate, mean tardy and standard deviation of lateness. At the same time, pre-shop sequencing rules, scheduling rules and protective capacity all affect the performance of BDDF method. It is necessary to select appropriate value according to the actual situation to better control the order due-date and avoid order delay. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanxi Agricultural Sciences is the property of Shanxi Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Petroleum Geology & Recovery Efficiency is the property of Petroleum Geology & Recovery Efficiency and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There are sufficient illumination resources and strong solar radiation in Shiyang River Basin. It is of great significance to estimate the total solar radiation accurately for agricultural production in Shiyang River Basin. In order to evaluate the simulation accuracy of common total solar radiation models in the Shiyang River Basin and determine the model suitable for the estimation of total solar radiation in the Shiyang River Basin, this paper selects 5 types of total solar radiation models based on the meteorological data of Shiyang River Experimental Station of China Agricultural University from 2014 to 2018. Five indexes, namely determination coefficient R2, mean absolute error MAE, root mean square error RMSE, consistency index d and overall evaluation index GPI are used to evaluate the suitability of the solar total radiation model based on different weather types. The results show that the comprehensive model based on percentage of sunshine, average daily temperature and relative humidity has the best simulation effect. In sunny weather, the cubic function A-P model has the best simulation effect. In cloudy weather, the comprehensive model has the best simulation effect, and the estimation model of total solar radiation in Shiyang River Basin based on weather combination is proposed, which provides a further model support for the estimation of total solar radiation in Shiyang River Basin. [ABSTRACT FROM AUTHOR]

Objective GB/T 17283-2014 is an important test method for measuring the dew point in natural gas and similar gases. At present, the standard does not stipulate the precision of the measurement results. This study determines the precision index of the dew point results, which provides the consistency evaluation basis for the users of the standard, and also can provide technical reference for revising the standard. Methods Using eight dew point instruments with different instrument manufacturers and models, the precision test is carried out through testing water-gas standard substance dew points under different pressure. Referring to the repeatability standard deviation of the determination results provided by the Russian standard GOST 20060-2021 Determination of water dew point temperature of natural gas, the precision index of the results of water dew point measured by cooling mirror condensate hygrometer was studied and determined. Results The limits of repeatability and reproducibility of measurement results are specified according to the measurement range of water dew point. The water dew point is -40.0 ℃≤tB≤-30.0 ℃, the limit of repeatability is ≤2.0 ℃, and the limit of reproducibility is ≤3.0 ℃. The dew point of water is -30.0 ℃

The state of health (SOH ) estimation of lithium batteries is low in accuracy while Gaussian process regression (GPR) is susceptible to local optimum and slow convergence speed. In this paper, the dragonfly algorithm (DA) is employed to optimize the hyperparameters of Gaussian process regression, and thus achieve accurate estimation of the nonlinear recession of lithium batteries. First, a number of features are selected from the charge/discharge cycle data of lithium batteries, including charging & discharging time and temperature change. Then, the correlation between these features and the SOH of lithium batteries is analyzed, and the features with higher correlation are selected as the health factors and taken as inputs to the model. The lithium battery degradation model is built by GPR and DA-GPR algorithms to predict the SOH of B0005, B0006 and B0007 on NASA battery datasets. The three sets of batteries are firstly charged in 1.5 A constant current mode (CC stage), and then changed to constant voltage mode when their voltage reaches the charging cut-off voltage of 4.2V (CV stage), and their charging is ended when the current of the batteries gradually decays to 20 mA. During the discharging process, the batteries are in 2A constant current mode until the battery B0005, B0006 and B0007 reaches the cut-off discharge voltage of 2.7 V, 2. 5 Vand 2. 2 V. Repeated charging and discharging will accelerate the aging process of lithium batteries. When the SOH of the test batteries is reduced to less than 70%, they reach their end of capacity and the experiment ends. The initial 75 cycles of B0005, B0006 and B0007 batteries are used as the training set and the remaining 90 cycles as the test set, in which the root mean square error (RMSE) for the Gaussian process regression (GPR) stands at 1.45, 0.285, and 2 768 4 respectively. In contrast, in the dragonfly algorithm-optimized Gaussian process regression (DA-GPR), the RMSE records at 0.119, 0.022 and 0.147, down by 91.79%, 92% and 94. 69% respectively. To verify the accuracy of DA-GPR prediction under limited number of samples, the first 10 cycles and the first 30 cycles of B0005 are selected as the training set, and the rest are used as the training set. Results show the RMSE of the first 10 cycles as the training set is 1.756 3, and that of the first 30 cycles as the training set is 0.150 71. To verify the generalizability of DA-GPR, B0006 and B0007 are chosen as training sets and B0005 as test set, whose RMSE reaches 0.74 4. In comparison with some other machine learning models, the RMSE of GPR reaches 1.545, of GA-BP (BP neural network optimized by genetic algorithm) 1 769 0, and of IGVO-SVR (support vector machine optimized by locust algorithm regression) 2.436. [ABSTRACT FROM AUTHOR]

BP neural network is characterized by fitting nonlinear data in machine tool thermal error modeling, but it has poor robustness. This paper proposes a PLS-BP neural network modeling method to effectively improve the prediction accuracy and robustness of the model. First, this method employs the partial least squares to reduce the dimensionality of temperature data and extract principal components, eliminating redundant information. Second, a regression mapping model is established on the basis of BP neural network and thermal error, and its prediction performance is compared with that of traditional BP models. The results indicate the PLS-BP modeling method achieves high prediction accuracy and robustness. It is also shown that the method is markedly superior to the traditional BP models, keeping the maximum mean and maximum standard deviation of residual standard deviation sets of prediction results below 3.13 jxm and 1.32 jxm respectively [ABSTRACT FROM AUTHOR]