Search Results (8)

Large-scale water network projects are a crucial approach for the rational allocation of water resources and addressing water resource crises. Reliable sustainability evaluation is essential to ensure the sustainable operation of large-scale water network projects. This study develops an improved Fuzzy Comprehensive Evaluation (FCE) method based on Game Theory weight fusion (GWF) for the quantitative evaluation of the sustainability of water network projects. By combining the Analytic Hierarchy Process (AHP), Entropy Weight Method (EWM), and Game Theory approach, the study integrates the advantages of both subjective and objective weighting methods to achieve the allocation of indicator weights; the sustainability of the Jiaodong Water Network Project was quantitatively evaluated by employing the improved FCE method. The results indicate that the resource and management dimensions are the two most critical factors affecting the sustainability of large-scale water network projects. Indicators with high weight such as per capita water resources, the rationality of the management system, and level of management intelligence are the primary risk factors affecting the sustainable operation of large-scale water network projects. The sustainability evaluation value of the Jiaodong Water Network Project is 82.83 points, which is classified as “high” sustainability. This validates the reliability of the evaluation indicator system and the method used. Full article

With the widespread application of artificial intelligence in real estate price prediction, model explainability has become a critical factor influencing its acceptability and trustworthiness. The Shapley value, as a classic cooperative game theory method, quantifies the average marginal contribution of each feature, ensuring global fairness in the explanation allocation. However, its focus on average fairness lacks robustness under data perturbations, model changes, and adversarial attacks. To address this limitation, this paper proposes a hybrid explainability framework that integrates the Shapley value and Least Core attribution. The framework leverages the Least Core theory by formulating a linear programming problem to minimize the maximum dissatisfaction of feature subsets, providing bottom-line fairness. Furthermore, the attributions from the Shapley value and Least Core are combined through a weighted fusion approach, where the weight acts as a tunable hyperparameter to balance the global fairness and worst-case robustness. The proposed framework is seamlessly integrated into mainstream machine learning models such as XGBoost. Empirical evaluations on real-world real estate rental data demonstrate that this hybrid attribution method not only preserves the global fairness of the Shapley value but also significantly enhances the explanation consistency and trustworthiness under various data perturbations. This study provides a new perspective for robust explainable AI in high-risk decision-making scenarios and holds promising potential for practical applications. Full article

In this paper, a coal–water–ecology (CWE) index system is firstly constructed based on an analysis of the current situation regarding coal mining, water resource utilization, and the ecological environment in an open-pit combined underground mining area. Three methods are used to determine the weights of each index in the system. Then, the TOPSIS model and coupling coordination degree model are adopted to construct the coordinated development model for CWE. Finally, the coordinated development status of CWE in the mine area is analyzed, and the next improvement measures are pointed out. The CWE index system contains 3 dimensions, 6 aspects, and 21 indicators. Combining the weights with game theory makes the weight coefficients more concentrated, reduces the dispersion of single weights, and makes the results of the fusion weights more reliable. The TOPSIS model and coupling coordination degree model can successfully characterize the coordinated development of CWE system factors. The proximity degrees of the CWE system in the study area show an increasing trend year by year. Although the coupling degree of CWE increases slowly year by year, it exhibits little coordination, with an average value of 0.4. Economic benefits, the water resource utilization rate, and the green land area are the three indices with the greatest weights. While ensuring the economic benefits of coal mining, coal enterprises should focus on improving the water resource utilization rate. The reduction in the green land area should also be emphasized in open-pit mining. Full article

In recent years, prefabricated buildings have developed rapidly in China. Compared with traditional buildings, prefabricated buildings require higher capabilities from partners in various aspects. However, due to the early stage of development of prefabricated buildings in China, the level of various enterprises varies greatly. How to evaluate partners scientifically and objectively is a realistic problem that needs to be solved urgently. In order to achieve economies of scale and promote the sustainable development of prefabricated buildings, this study proposes a novel evaluation model for strategic partner selection based on the cloud model and improved Dempster–Shafer (D-S) evidence theory. First, using a literature review and field research method, a strategic partner selection index system is developed that can reflect the characteristics of prefabricated buildings. To address the fuzziness and randomness of the traditional membership function, the cloud model is applied to calculate the membership value between the test samples and the benchmark cloud, which is subsequently transformed into basic probability distribution in the evidence theory. Furthermore, to mitigate the paradox of evidence fusion often encountered in traditional evidence theory, this model combines both the subjective and objective weights of evidence by game theory, and the conflicting evidence is corrected and fused according to the combination weight. Additionally, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to further optimize the strategic partners of prefabricated buildings. Finally, the optimal order obtained from the case analysis is S₁ > S₂ > S₄ > S₃ > S₅, and the evaluation results are consistent with the actual situation, which verifies the effectiveness and superiority of the proposed model in resolving the evidence conflict and selecting strategic partners. The research results have certain reference significance for optimizing the selection mechanism of prefabricated building strategic partners and guiding partners to establish long-term and stable cooperative relations. Full article

Due to the complex hydrogeological conditions and water hazards in coal mines, there are multiple indexes, complexities, incompatibilities, and uncertainty issues in the risk evaluation process of coal-mine water hazards. To accurately evaluate the risk of coal-mine water hazards, a comprehensive evaluation method based on extension theory, game theory, and Dempster–Shafer (DS) evidence theory is proposed. Firstly, a hierarchical water-hazard risk-evaluation index system is established, and then matter-element theory in extension theory is used to establish a matter-element model for coal-mine water-hazard risk. The membership relationship between various evaluation indexes and risk grades of coal-mine water-hazard risk is quantified using correlation functions of extension set theory, and the quantitative results are normalized to obtain basic belief assignments (BBAs) of risk grades for each index. Then, the subjective weights of evaluation indexes are calculated using the order relation analysis (G1) method, and the objective weights of evaluation indexes are calculated using the entropy weight (EW) method. The improved combination weighting method of game theory (ICWMGT) is introduced to determine the combination weight of each evaluation index, which is used to correct the BBAs of risk grades for each index. Finally, the fusion of DS evidence theory based on matrix analysis is used to fuse BBAs, and the rating with the highest belief fusion result is taken as the final evaluation result. The evaluation model was applied to the water-hazard risk evaluation of Sangbei Coal Mine, the evaluation result was of II grade water-hazard risk, and it was in line with the actual engineering situation. The evaluation result was compared with the evaluation results of three methods, namely the expert scoring method, the fuzzy comprehensive evaluation method, and the extension method. The scientificity and reliability of the method adopted in this paper were verified through this method. At the same time, based on the evaluation results, in-depth data mining was conducted on the risk indexes of coal-mine water hazards, and it was mainly found that 11 secondary indexes are the focus of coal-mine water-hazard risk prevention and control, among which seven indexes are the primary starting point for coal-mine water-hazard risk prevention and control. The groundwater index in particular has the most prominent impact. These results can provide a theoretical basis and scientific guidance for the specific water-hazard prevention and control work of coal mines. Full article

Unmanned aerial vehicle (UAV) swarm coordinated confrontation is a hot topic in academic research at home and abroad, and dynamic maneuver decision-making is one of the most important research fields for UAV countermeasures. Aiming at the complexity, uncertainty and confrontation of UAV cooperative confrontation, concepts such as relative advantage degree and advantage coefficient are introduced, and game theory is used as a framework to construct a dynamic non-zero-sum game UAV cluster cooperative confrontation decision-making model, and finally convert it into an optimization problem. On this basis, using the Nash equilibrium solution method of multi-strategy fusion particle swarm algorithm, by introducing adaptive inertia weight and local mutation strategy, while enhancing the diversity of the population, it can ensure the local accurate search ability of the particle swarm. The simulation results of the example are verified. The effectiveness of the proposed model and method is confirmed. Full article

Energy limitation is one of the intrinsic shortcomings of wireless sensor networks (WSNs), although it has been widely applied in disaster response, battlefield surveillance, wildfire monitoring, radioactivity detection, etc. Due to the large amount of energy consumed for data transmission, how to prolong the network lifespan by designing various hierarchical routing protocols has attracted more and more attention. As a result, numerous achievements have emerged successively. However, these presented mechanisms can rarely guarantee the satisfactory quality of service (QoS), while lowering the energy cost level of WSNs. Meanwhile, invulnerability is undoubtedly an excellent quantitative index to assess QoS. Therefore, it is critical to develop a practical routing method to optimize network lifetime by considering both invulnerability and energy efficiency. Game theory is suitable for such a critical problem as it can be used in node or at network level to encourage the decision-making capabilities of WSNs. In this paper, a novel invulnerability-aware clustering routing algorithm (IACRA) using game-theoretic method is proposed to solve the predicament. The core features of the addressed game-theory-based routing protocol include integral invulnerability awareness, optimal cluster head selection in hierarchical routing, distance-aware cluster head discovery, and cluster rotation update mechanism for lifetime optimization. Particularly, the integral network invulnerability based on weighted fusion is constructed for further defining the profit model by combining the invulnerability indicators used to evaluate the local and whole network. Meanwhile, the optimal probability function of every node elected as CH in per cluster is established through the game between invulnerability and node energy consumption. In addition, the cluster update mechanism base on cluster rotation is proposed to avoid the rapid death of nodes with large energy consumption for maximizing network lifetime. The experimental results indicated a significant improvement in energy balance as well as in invulnerability compared with the other three kinds of well-known clustering routing protocols including GEEC (Game-theory-based energy efficient clustering routing protocol), HGTD (Hybrid, game-theory-based distributed clustering protocol), and EEGC (Efficient energy-aware and game-theory-based clustering protocol). Concretely, at the 400 communication rounds, the invulnerability of IACRA was higher than that of GEEC, HGTD, and EEGC by 77.56%, 29.45% and 15.90%, respectively, and the average residual energy of IACRA was 8.61%, 18.35% and 6.36% larger than that of GEEC, HGTD, and EEGC, respectively. Based on these results, the proposed protocol can be utilized to increase the capability of WSNs against deterioration of QoS and energy constraints. Full article

In the case of surface water pollution, it is important and necessary to accurately assess the level of contaminated water and ensure the safety of drinking water for people in disaster areas during floods. However, for the assessment of the strict requirements of drinking water, traditional assessment methods still have some limitations, such as low precision and rationality. In order to overcome these limitations, in the light of the theory of set pair analysis and variable fuzzy set, we propose an improved variable fuzzy set pair analysis method (IVFSPA), which combines the analysis framework of variable fuzzy set and set pair analysis, and has made some improvements to the fusion architecture. Firstly, we present a novel game theory comprehensive weighting method, in which the objective entropy method and the subjective analytic hierarchy process(AHP) method employed to obtain the reasonable weight. Then, based on the Nemerow index method, we improve the arithmetic form of “ $P_i$ ” (Equation P) to replace the fuzzy comprehensive evaluation method. Furthermore, we design a double judgment mode of combining the principle of maximum membership degree with the positive and negative relationship between the standard value and the measured value, which can accurately judge the evaluation level of surface water quality. Finally, to validate and verify the effectiveness of the proposed method, experiments was conducted at the representative river collection sections of Nanking, China, employing water quality data of 14 sampling sections in their rivers in Nanking during the 2017 flood. In terms of performance metcrics of precision and rationality, based on the values of “TP”, “NH₃-N”, “Pb”, “AS” and “KMnO₄” of “Ch-lh section/Chuhe gate” are 0.415, 3.77, 0.07, 0.23 and 7.12, respectively, the level of Ch-lh section/Chuhe gate is that the IVFSPA is Class V and the rest are class IV. Results of experiments show that our IVFSPA method can achieve a good performance, compared with other traditional methods. Full article