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The construction and promotion of emission trading information platform makes it possible for enterprises to collect and use emission rights and other data. How to conduct game analysis for industrial enterprises' emission trading under data driven has become an effective basis and inevitable trend to assist enterprises to achieve emission reduction and optimal decision-making. However, existing game methods are not used for comprehensive optimal decision for enterprises based on these data. Therefore, this paper integrates dynamic game and data to effectively solve optimal choice in the process of emission trading among industrial enterprises. The bargaining dynamic game model and forward reasoning method are proposed to realize the game analysis of emission trading among enterprises in the secondary market based on the data mining or evaluation of pollutant emissions, market price and marginal revenue of emission rights and initial emission rights by Support Vector Regression (SVR), Linear Regression (LR) and Analytical Hierarchy Process (AHP). Taking six industrial enterprises in Tianjin as an example, this paper analyzes the optimal trading price, trading volume and object of emission trading among different enterprises under different loss factors.

The scenario-based test method is the research hotspot of automated vehicle (AV) validation and verification (V&V), and testing with hazardous scenarios is of important means. An Optimization Searching (OS) method for enhanced generation in hazardous scenarios is proposed in this paper to efficiently explore functional boundary scenarios in a huge logical state space. The method is computationally tractable, and its generated experimental parameters are optimized using past test results. The method includes five essential modules. The Exploration and Exploitation module uses the Multi-arm bandit method to obtain the greatest sum of the TTC⁻¹ (Time To Collision). The Parameter Moving Probability Determination module uses an analytic hierarchy process to ensure that influential parameters are more likely to move. The Step Size Determination module is built with Levy-step to find a greater number of hazardous scenarios. The Memory Function module is used to avoid repeat experiments that can reduce computing efficiency. The Result Analysis module creates a hazard parameter space for subsequent tests. We tested an ACC (Adaptive Cruise Control) algorithm with a specified logical scenario in the virtual environment built by PreScan. The results showed that the OS method can effectively discover the dangerous range with the tested ACC algorithm, and its test speed can reach more than five times that of an exhaustive algorithm without prior knowledge.

For Intrusion Detection Systems (IDSs) in Vehicular Ad Hoc Networks (VANETs), single-objective optimization algorithm has inherited limitations for the feature selection problem with the multiple objectives. Moreover, the imbalanced problem commonly exists in various datasets. Thus, in this paper, a feature selection algorithm based on a many-objective optimization algorithm (FS-MOEA) is proposed for IDSs in VANETs, in which Adaptive Non-dominant Sorting Genetic Algorithm-III (A-NSGA-III) serves as the many-objective optimization algorithm. Two improvements, called Bias and Weighted (B&W) niche-preservation and Information Gain (IG)-Analytic Hierarchy Process (AHP) prioritizing, are further designed in FS-MOEA. The former is used to counterbalance the imbalanced problem in datasets by assigning rare classes higher priorities, while the latter is employed to search the optimal feature subset for FS-MOEA. In IG-AHP prioritizing, a more distinct measurement, i.e. average IG, is used as the dominant factor to guide the decision analysis of AHP. Experimental results show that the proposed FS-MOEA can not only improve the performance of IDSs in VANETs but also alleviate the negative impact of the imbalanced problem.

This paper presents an integrated model for optimization of laser cutting process of St-52 steel plates with multiple performance characteristics using Goal Programming (GP), Analytic Hierarchy Process (AHP), and Response Surface Methodology (RSM) approaches. In this study, optimum levels of the laser cutting process input parameters namely, material thickness, cutting speed, laser power, and assist gas pressure are obtained. For optimization purposes, four different surface roughness types of a cut surface, surface hardness, cutting time, and heat-affected zone (HAZ) of the cut surface are considered as performance outputs (responses) in this study. Optimization of multiple performance objectives (responses) requires obtaining regression functions with RSM first, and then weighting the regression functions using the AHP and finally combining the multiple functions into a single overall goal within a GP model and solving the model to optimize the laser cutting process. The study clearly shows that the presented optimization model is flexible enough to optimize the laser cutting process for various scenarios and conflicting priorities.

This paper exemplifies the feasibility of expanding a multi-criteria decision-making (MCDM) method to select optimum process parameters during the wire electrical discharge machining (WEDM) of nitinol. The application potential of combined desirability function analysis (DFA) and analytical hierarchy process (AHP) has been reported. Nitinol, a shape memory alloy (SMA), can memorize or retain its original shape when subjected to thermo-mechanical or magnetic loads. Four key input variables, like pulse on time ([Formula: see text], pulse off time ([Formula: see text], wire tension (WT), and wire feed (WF) have been studied to optimize three correlated responses, like kerf width, material removal rate (MRR), and surface roughness ([Formula: see text]. Process parameter permutations [Formula: see text]s, [Formula: see text]s, [Formula: see text] kg-F and [Formula: see text][Formula: see text]m/min were found to yield the optimum results. For the desired kerf width, MRR and [Formula: see text], the optimum process parameters were also achieved expending Taguchi’s signal-to-noise ratio. Validation results affirmed that the MCDM approach, AHP–DFA is a proficient strategy to select optimal input parameters for a preferred output eminence for WEDM of nitinol.

As the only resort to realize the low-carbon utilization of high-carbon fuel, CCUS has attracted considerable attention from experts in various fields. However, the global demonstration of CCUS has not gone well for several reasons. Multiple technical options, diverse combinations of schemes and complex evaluation systems of CCUS are crucial reasons. Another key point is the diverse concerns of key stakeholders involved in the deployment of CCUS, leading to decision-making difficulties. Thus, in this paper, with the aid of the analytic hierarchy process method, five representative cases are defined, compared and evaluated from the technical, economic and policy perspectives. The evaluation results and corresponding interpretations are given from diverse perspectives. By adopting this evaluation method and establishing a comprehensive model, decision makers can clarify their requirements, carry out multi-dimensional evaluation, and obtain inspiration to make corresponding judgements or decisions for early CCUS demonstration projects, which is conducive to promoting the progress of CCUS demonstration projects.

Adaptability evaluation of reservoirs needs to be performed before natural gas flooding. However, the current evaluation methods consider the reservoir pressure and minimum miscible pressure (MMP) as separate parameters to evaluate the miscibility, which ignores the correlation between reservoir pressure and MMP. Also, the effect of reservoir pressure on injectivity is also neglected, while higher pressure than MMP may not improve the miscibility but increase the difficulty of gas injection. Furthermore, evaluation range of each index is inconsistent. Therefore, this paper proposes an improved evaluation system by introducing the miscible ability and optimizing the evaluation criteria to better evaluate the adaptability of natural gas flooding in enhancing oil recovery. The miscible ability is newly defined to evaluate the impact of reservoir pressure on miscibility, and multi-level evaluation model is further developed which includes 12 indexes based on reservoir/fluid/rock properties. The evaluation criteria are established by optimizing parameter intervals. The adaptability of BQ Oil field is assessed using Analytic Hierarchy Process (AHP) and fuzzy evaluation. Field application validates the reliability of the proposed evaluation system. It can be used to quickly evaluate the adaptability of natural gas flooding, which could improve success rate of natural gas flooding and reduce the costs.

In civil engineering and architecture, sustainability requires energy optimization minimizing the energy amounts needed for heating and cooling. Revitalization of built heritage, except the renewal of the original identity, and preservation through adaptive reuse, must meet the requirements set within the framework of energy postulates. Given that the physical interventions for improvement of energy efficiency can affect the visual appearance of the building, energy retrofitting of built heritage under the protection regime represents a challenge in the management of cultural heritage. The paper aims to identify the most optimal measures to be applied to increase energy efficiency, depending on the protection level, using the fuzzy Analytic Hierarchy Process (AHP) method. Results show that for the highest protection level, the maximum degree of optimism indicates complete preservation of building identity, favoring indicators related to the technical systems, while for the medium protection level, all degrees of optimism favor internal insulation of thermal barriers and collector walls. Despite the allowed interventions for the lowest protection level, the optimistic view suggests alternative solutions not to greatly undermined identity. At the maximum degree of optimism, the application of indicators for technical systems dominates, which only in the last resort makes changes to the building.