Fuzzy Gray Correlation Analysis Research Articles

Structural optimization of thermal management system for bionic liquid cold battery based on fuzzy grey correlation analysis

An energy-efficient battery thermal management system with efficient enhanced heat transfer characteristics, low power consumption and backflow inhibition performance is of great importance for electric vehicle power batteries. Based on the design of the Tesla valve and inspired by bionics, a new type of bionic blade-like mini-channel liquid cold plate with high efficiency, low power consumption and certain anti-reverse flow performance was proposed. Firstly, the initial liquid-cooled plate thermal simulation model at 5C discharge was established by CFD method and its reliability was verified by experiment. Then, orthogonal tests and fuzzy correlation analysis (FGRA) were used as evaluation methods to analyze the effects of four structural parameters (inner angle α, circumcenter angle θ1, circumcenter angle θ2, and channel height d) on the average temperature, heat transfer coefficient, and friction coefficient. The results show that the variation of the channel height d had the highest degree of influence on the mean temperature (Tave) and friction coefficient f, and that the internal angle α had the highest correlation with the heat transfer coefficient h. Finally, based on the optimization results, a better model within the range of values of each factor was obtained. When α = 25°, θ1 = 90°,θ2 = 75°, and d = 1.2 mm, Nu was increased by 0.932 (95.08 %), and ΔP was decreased by 501.686 Pa (84.74 %).The results of the optimization were shown in the following table.

Application and Implications of Artificial Intelligence Technology in Basketball Coaching Decision Making

Abstract The proliferation of artificial intelligence (AI) technologies is significantly enhancing the precision and efficacy of decision-making in basketball. This study focuses on players from the men’s basketball team at School A, employing AI to model their sports postures, collect athletic performance data, and analyze physiological metrics in real time. By utilizing fuzzy gray correlation analysis, the research aims to identify the factors influencing basketball game outcomes, thereby informing tactical decisions for coaches. Moreover, this paper compares the proposed analysis method with other correlation techniques to evaluate its relative superiority. The findings indicate that post-training, the serum levels of all ten athletes exceeded 400 U/L. Yet, the creatine kinase (CK) levels remained below 6.8 mmol/L, and the urine specific gravity surpassed 1.05, suggesting that the training intensity was high but within the athletes’ physiological tolerances. With a correlation coefficient of 0.4, the study confirms a positive impact of game outcomes on the coach’s tactical adaptations. This underscores the utility of integrating AI systems into basketball to facilitate timely and effective decision-making by coaches.

Multi-objective impact mechanism on the performance characteristic for a diesel particulate filter by RF-NSGA III-TOPSIS during soot loading

Diesel particulate filter (DPF) provides an effective control method for particulate matter (PM) emissions from diesel vehicles. In the PM trap process of DPF, pressure drop and filtration efficiency present conflicting relationships as the main indicators of the comprehensive trap performance. To fully optimize the comprehensive trap performance of DPF, this research develops a hybrid multi-objective optimization approach of FGRA-RF-NSGA III-TOPSIS. Specifically, critical structures are selected from DPF structural features by fuzzy grey correlation analysis (FGRA). Three machine learning (ML) models are trained on the computational fluid dynamics (CFD) model dataset to relate the critical structures to the initial filtration efficiency and pressure drop. Then, statistical indicators are introduced to evaluate three ML models, and the best-performing model – The random forest (RF) model is selected as the input of the optimization algorithm. Finally, a hybrid Critic-TOPSIS approach is used to select the most ideal solution from the Pareto frontier obtained by the NSGA III as the output of the optimization results. The optimized DPF reduces the pressure drop by 49.84 % and improves the initial filtration efficiency by 49.31 % compared to the original DPF under standard operating conditions. The optimization effect is more significant at high-speed and high-load conditions.

Effects of the different phase change materials on heat dissipation performances of the ternary polymer Li-ion battery pack in hot climate

To improve the heat dissipation performance of the Ternary Polymer Li-ion Batteries(TPLBs) in hot climate, a heat dissipation method including different PCMs (Paraffin, 10% GNP + Paraffin, 10% EG + CPCM) was established, and orthogonal test and fuzzy grey correlation analysis method were applied to investigate the heat dissipation effects of the TPLBP in hot climate. The results shown that the TPBP with 10% EG CPCM is of heat dissipation characteristics and thermal security (namely the temperature difference is less than 5K), it makes sure the safety operation of new energy vehicles under 3C in hot climate. And the fuzzy grey correlation values between the thermal conductivity λ of the PCM and the time τ0 of melting point appearance of the PCM in the TPLBP is of a maximum value of 0.5660, and the fuzzy grey correlation values between the discharge current I and the time τ0 of melting point appearance of the PCM in the TPLBP is of a minimum value of 0.3386. Therefore, the discharge current I has the greatest effect on the liquid phase composition ω of PCM, but also has the least effect on the time τ0 of melting point appearance of the PCM in the TPLBP.

Deterioration evaluation of cerium-based catalytic diesel particulate filter based on fuzzy grey correlation analysis

This study simulated the composite regeneration process of a Catalyzed Diesel Particulate Filter (CDPF). The degradation performance was evaluated using the maximum wall temperature as the benchmark. The orthogonal experiment design and fuzzy grey correlation analysis approach were employed to analyze the effect of various factors, including regeneration temperature, NOx mass, catalyst coating amount, SO2 concentration, oxygen concentration, and exhaust flow rate, on the degradation of the CDPF. A comprehensive analysis of the factors was conducted, yielding important insights into the key factors that can be leveraged to optimize the system. The results reveal that these six operating parameters are the primary drivers of the CDPF’s performance degradation, with the NOx mass having the greatest impact on the maximum wall temperature.

Multi-Source Information Fusion Correlation Analysis of Bedrock Deterioration on Slopes Under Leaching Erosion

To explore the effect of leaching erosion on the deterioration mechanism of ionic rare earth slope bedrock. The E-TOPSIS method and fuzzy grey correlation method were used to fuse and analyze the multi-source heterogeneous information such as porosity, pH, mass, volume, density, P-wave and characteristic strength of bedrock specimens. The dominant response parameters of bedrock deterioration of slopes under leaching erosion were obtained, and the multi-source information fusion correlation analysis model was established. The results show that compared with the basic physical parameters of bedrock, the influence of leaching erosion on the pore structure of bedrock is more significant; the pore space and leaching solution pH show obvious dominant responsiveness in the E-TOPSIS analysis with soaking duration. Basically, from the results of fuzzy grey correlation analysis, the micropore of bedrock specimens continued to increase after the decrease in the early stage of soaking, and the porosity varied significantly; the micropore and porosity of bedrock specimens had the highest correlation with the characteristic strength of bedrock, followed by the pH of leaching solution.

Adaptive carrier fringe pattern enhancement for wavelet transform profilometry through modifying intrinsic time-scale decomposition.

The uneven background illumination and random noise will degrade the quality of the optical fringe pattern, resulting in reduced accuracy or errors in phase extraction of wavelet transform profilometry (WTP). An adaptive fringe pattern enhancement method is proposed in this paper, which can effectively solve the above problems and improve the robustness of WTP. First, a modified intrinsic time-scale decomposition (MITD) algorithm is used to decompose each row of the fringe pattern adaptively, which can obtain a set of reasonable and pure proper rotation components (PRCs) with a frequency ranging from high to low and a monotonic trend. The MITD algorithm can overcome the mode mixing problem while ensuring the completeness of decomposition. Then, based on the obtained pure PRCs, an innovative background-carrier signal-noise automatic grouping strategy is proposed. Specifically, weighted-permutation entropy (WPE) is adopted to handle noise removal, and fuzzy gray correlation analysis (FGCA) is used to separate the background and carrier signal. Finally, the desired phase information can be easily and accurately extracted from the enhanced carrier signal component by a direct wavelet ridge detection method. Both the simulation and experimental results demonstrate the effectiveness and functionality of the proposed method.

A New Calculating Method of Pressure Response Time of Pneumatic Brake Pipe Based on Experiments

Air brake system is one of the common braking methods for buses and trucks; its excellent performance guarantees the safety of the vehicle and the stability of the braking. As an important part of the pneumatic brake system, the brake pipe is an important factor influencing the pressure response time of the pneumatic brake system. Based on the exploratory experiment of pneumatic brake pipe, the influence of pipe length, pipe diameter, inlet sonic conductance, initial pressure, and supply pressure on pipe pressure response time was analyzed by fuzzy gray correlation analysis method. The results show that tube length is the most important factor affecting the pressure response time. Combined with the analysis results of gray correlation degree, the experimental scheme of the response time of the pneumatic brake pipe was designed by the response surface experimental design method. Based on the multiparameter analysis method, the influence of the experimental parameters on the pipe pressure response time was analyzed. Based on the experimental data, the form of calculation formula is derived by dimension analysis method, which provides a theoretical basis for the selection of pneumatic brake pipes and the design of air brake system.

An integrated approach for multi-objective optimisation and MCDM of energy internet under uncertainty

Energy Internet represents a critical breakthrough which is regarded as the synthetic product of information communication technologies and energy technologies. It is highly conducive to providing possible solutions for transforming energy management methods, reducing carbon emissions and achieving sustainable development. The extensive attention of scholars has been drawn to the progress of Energy Internet. However, the multi-objective optimisation and multi-criteria decision making (MCDM) for Energy Internet considering uncertainty still has some problems. (1) The actual number of optimisation objectives for Energy Internet design is more than two so that it is difficult to adopt conventional intelligence algorithms to solve it. (2) Most intelligence algorithms for double-objective optimisation model are not desirable. (3) The MCDM process of Energy Internet is not considered systematically. To solve these problems, an integrated approach combining improved great deluge algorithm (GDA), evidence reasoning (ER), interval algorithm, and fuzzy grey correlation analysis for multi-objective optimisation and MCDM of Energy Internet considering uncertainty is proposed in this paper. The practicality and effectiveness of the proposed approach are illustrated by a visual case study of Energy Internet design.

Comprehensive analysis on influencing factors of composite regeneration performance of a diesel particulate filter

In order to effectively improve the composite regeneration performance of the diesel particulate filter in vehicle, a fuzzy gray correlation analysis model based on the composite regeneration influencing factors of diesel particulate filter was established using the cosine value of fuzzy membership and Euclidean distance formula. And, on the basis of experimental data from three‐dimensional computational fluid dynamics simulation, the fuzzy gray correlation analysis on important degree of characteristic indexes, which has influence on the composite regeneration performance of diesel particulate filter, was conducted. Moreover, the method of Lagrange function was used to solve the fuzzy gray affiliate degree based on the results of this fuzzy gray correlation analysis. The effectiveness indexes of overall performance of the diesel particulate filter composite regeneration time, regeneration peak temperature and regeneration efficiency were also obtained. The results showed that the amount of ceria‐based additive had the greatest influence on the regeneration time among all the characteristic performance indexes of diesel particulate filter composite regeneration. Similarly, it could be concluded that the exhaust oxygen concentration and exhaust temperature respectively had the greatest influence on the regeneration peak temperature and regeneration efficiency. In addition, the regeneration time had the greatest influence on the overall performance of diesel particulate filter composite regeneration while the regeneration efficiency took the second place and the influence of the regeneration peak temperature was the minimum. The results of this article showed theoretical significance and reference value for optimization analysis and control of diesel particulate filter composite regeneration process. © 2015 American Institute of Chemical Engineers Environ Prog, 35: 882–890, 2016