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Due to natural conditions in northern China, heat power is the main energy supply, and there is a large proportion of wind power connected to the grid. During the heating period in winter, combined heat and power (CHP) unit operates in the "determining power generation by heat" mode, which coincides with the time when wind power is abundant, resulting in serious wind abandonment in the system. P2G is adapted to convert excess wind power to natural gas in order to promote wind power consumption and decoupling to "determine power generation by heat". Aiming at the uncertainty of wind power output, this paper uses Autoregressive Integrated Moving Average model (ARIMA) model and Latin hypercube sampling to generate a large number of scenes, and K-means clustering algorithm to form typical scene sets. Considering the structure of the distribution network and the gas network, a multi-energy flow calculation model is established. Based on the energy hub model, a day-ahead optimal dispatch model of the Electricity-Gas-Heat-Cooling Integrated Energy System (EGHC-IES) is established, taking into account the comprehensive demand response on the user side, wind power output forecast and energy storage. The results of the case studies shows that the optimized dispatching solution can promote the consumption of renewable energy and improve energy efficiency.

This paper proposes an unmanned aerial vehicle (UAV) flight tracking Control method based on BP neural network to improve the proportional-integral-differential (PID) control of four-rotor UAV flight tracking control. The traditional PID control cannot be updated in real time. $K_{p},K_{l},K_{d}$ parameters, BP neural network algorithm error convergence speed is slow, training learning is easy to fall into local optimal value, and so on. A control method combining BP neural network and PID control using genetic algorithm (GA) to optimize the additional inertia term is the designed. Through the global search ability of the genetic algorithm, the weight and threshold of the BP neural network are adjusted to improve the system convergence speed and system accuracy. Simulation analysis shows that comparison between the traditional PID and BP neural network-PID control, the proposed method improves the robustness and dynamic performance of the system, improves the convergence accuracy and convergence rate, and thus the attitude of the drone. Control adjustment tracking has a good practical reference value.

This paper presents a method for reliability assessment of offshore oil platform power systems. Firstly, according to the environment and fault factors of the components on the platform, the reliability model of each offshore component is established. In order to evaluate the reliability of different types of platforms, a multi-state equivalent generator set model is established. Secondly, the breadth-first algorithm and Dijkstra algorithm are combined to calculate the power loss under the current state of the system in the state evaluation. Based on the reality of offshore platform, the Preferential trip sequence in EMS system is used to replace the load shedding result, which improves the accuracy and practicability of evaluation of offshore platform project. Finally, a platform in an oil field group in China is taken as an example to verify the accuracy and validity of the proposed method.

Due to the lack of a unified and comprehensive description of the dynamic disaster process monitoring, it is a great challenge to quickly and effectively share and discover more linked information resources in sensor web for the improvement of decision-making efficiency. A sensor web resource ontology for the dynamic disaster process monitoring was proposed in this paper, which can focus on the characteristics of the observation resources for diverse applications during different monitoring processes. To verify the feasibility of the method, case studies were conducted, including the semantic modeling of the in-situ monitoring and the remote sensing monitoring for flood disaster processes. The results demonstrated the effective sharing of various observation resources with different processes for environmental monitoring.

Object tracking task faces serious challenges when a desired target is in complex circumstances such as obstacle occlusion, pose variation, illumination change and motion blur. Despite lots of excellent tracking algorithms have been proposed, many issues remain to be addressed. In this paper, we propose a novel object tracking algorithm to combine both Enhanced Perception Hash and Coarse-to-fine Sliding Window search strategy. First, we calculate the feature template of target by using the perception hash approach integrating Fast Fourier Transform (FFT). We make a FFT on the target area in a frame and only retain low-frequency part to save storage. Moreover, the new template is generated by fusing the templates from the current and previous frames, thus it is robust to the severe deformation and drastic variation problem. Second, we propose a coarse-to-fine sliding window search strategy to provide potential target candidates efficiently. Based on this strategy, our tracking algorithm can implement an effective online detection for target. Extensive tests on thirteen videos are conducted and demonstrate that our approach achieves promising performance as compared to the state-of-the-art methods.

Radar emitter's position can be estimated by dual satellites location system utilizing DTO (differential time offset) and DFO (differential frequency offset). Signal model received by dual satellites is given and the influence to signal accumulation by relative motion is analyzed in this paper. Then the upper limit of accumulated pulses' number is given. The Cramer-Rao lower bounds (CRLB) of DTO and DFO estimation of radar pulse signal are derived based on the CRLB of continuous signal. By Mount-Carlo simulations, the conclusions drawn in this paper are proved. The results can provide a theoretical basis for selection of accumulation duration and analysis of parameter estimation accuracy.

An integrated sensor which combined tension measurement with length measurement of winch cable was designed. The length was measured by specific measurement wheel and photoelectric encoder, both of which maintained rolLing state with winch cable, while tension can be measured in an indirect way with the shear strain, after designing measurement wheel axle to be axle pin type weighing-sensor. Practice proved that the sensor has such strongpoint as topping measure precision, lower bit error rate, high performance-price rate. This paper introduced the integrated sensor's work principle, the method of design and calculation for sensor elastomer, besides these, it also put forward some problems which sHould be noted in the process of designing and applying on the basis of analyzing origins of different kinds of measure error.

Due to safe working requirement of well testing truck, a type of multifunctional virtual real-time general monitoring system is developed on the basis of deeply studying on the measuring principle of well testing truck, which can measure pulLing force, tension gradient, Lifting speed and well depth of the winch cable of well testing truck at the same time, and has the function of real-time condition analysis and monitoring, multi-parameter syncs synthetic, historical data playback, intelLigent alarming of underground instrument such as meeting resistance and meeting sticking, Liquid level, flow, near the wellhead and so on. This system provides not only a measuring platform but also a reLiable guarantee for safety production of well testing truck.

The purpose of this research was to find out the laws of community structure in quantity for study sustainable management of evergreen broad-leaved forest. The structure models were modeled by computer and the following laws were found: (i) With the increase of height-class or diameter-class, the number of trees and the number of species of evergreen broad-leaved forests shows the distribution of “reversal J type” in the total, the south-slope and north-slope. These relationships can be described by negative exponential equation. (ii) The relationship between the number of species richness and the number of trees shows the obvious positive correlation and can be described by power function equation. (iii) Different slope directions of evergreen broad-leaved forest have different the structure features. On the whole, south-slope is closer to the total, and north- slope is slightly away. These laws will lay a foundation for the study on exploiting, forest cutting and regenerating of the evergreen broad-leaved forest in future.

The purpose of this design was to provide information consultation and diagnosis, decision support and technical services functions on sustainable management of rural collective forests for farmers. The expert system was designed and built by applying expert system's basic principles in the Web environment. The general structure of system, knowledge base management and inference engine were designed, furthermore, examples of system operation were given. This system was composed of 8 main modules, i.e. related knowledge and policies for forestry, the compilation of forest management plan, forest tending, stand transformation, forest fire prevention and controls of diseases and pests, forest by-products utilization, cutting and regeneration, and knowledge base management. It will help the sustainable management of rural collective forests for farmers.

At present, the intersection and fusion of different disciplines need to tackle a joint research. By the cooperation of different disciplines, knowledge innovation has become the important element of innovation in research organization. Communication management of knowledge innovation is one of the most essential management systems, which is beneficial for members in research organization to share information. It is of great significance for knowledge innovation and research innovation with communication management. This paper discusses the effect of specific communication means in knowledge innovation systems and precisely explores the dynamic relationship among the communication management's elements and knowledge innovation, and at last constructs knowledge innovation models of communication management in research organization.

The research and development (R&D) investment timing decision-making problem is studied based on option game theory in this paper. The existence and inequality of two businesses operating costs are assumed, and jump diffusion is used to describe sudden events. The duopoly option game model is established to obtain the R&D investment value function and the critical value to invest. The game strategy and profit matrix of both firms are constructed, to discuss the existing forms of equilibrium, so that each timing for sequential equilibrium, preemptive equilibrium and simultaneous equilibrium is achieved.

Effective knowledge management and innovation in research teams is a key to successful team performance. It is of great significance for knowledge management and research innovation with communication means. In this paper, we compare different concepts of knowledge management and innovation and then discuss the relationship between the effect of knowledge management and innovation and the free degree of member's communication. Thereafter, we precisely explore the effect and application of specific communication means. Finally, we construct the application models of knowledge management and innovation based on different communication means in research teams.

Nowadays, the joint research with the intersection and complementation of various disciplines has become the new trend of global research development. Research organizations need to find new managing mechanism and take the advantages of researchers at each level to approach to innovation. So far, the application of knowledge management and communication management in business management turns into the focus in academic management circle. Based on the definitions and characteristics of knowledge management and communication, we construct the cooperation model of organization's dynamic communication means in this research. Furthermore, on the basis of system dynamics theory, we analyze the system dynamic relationship between knowledge management and communication management, construct a framework of the fusion model of knowledge management and communication management, discuss the effect and application of specific communication means in two management systems and precisely explore the implementation of two kinds of management in the process of research.

Continually extended scientific research needs more cooperation among different disciplines. An outstanding research team needs to develop a set of management models to support effective management. Knowledge management, as a completely new management model and management theory, has been successfully applied to knowledge organizations in enterprises and has formed a set of relatively perfect theoretical methods. This paper firstly sets up a model of dynamic harmonious cooperation among research teams according to their characteristics and a frame model of knowledge management based on the analysis of similarities and differences between knowledge organizations in enterprises and research teams. Then it presents the application of knowledge management into the process of research projects in detail. Finally, it discusses the learning mechanisms of individuals in a research team as well as of the whole team to improve the team's abilities of learning, applying, researching and developing.