Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). …”
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Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
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Optimizing demand charge of data center base on PE method by Yan HUANG, Peng WANG, Gao-hui XIE

“…Demand charge and energy charge are the two main components of data center electricity cost,previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot,work-load,service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted,PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.…”
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Optimal Configuration Method for Electric-thermo-hydrogen System Considering Safety Risks by Chouwei NI, Yang CHEN, Xuesong ZHANG, Da LIN, Kaijian DU, Jian CHEN

“…Furthermore, the safety risk coefficient is used to convert the safety risk of the hydrogen storage tank into the objective function. The optimal configuration model of the ETHS is then established with the system investment cost, operation cost, and safety risk as optimization objectives, and the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm is employed to solve the model. …”
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Robust Optimization of Active Distribution Networks Considering Source-Side Uncertainty and Load-Side Demand Response by Renbo Wu, Shuqin Liu

“…The iCCG algorithm improves the computational efficiency by 35.2% compared with the traditional CCG algorithm, which verifies the effectiveness of the model in coping with the uncertainties and improving the economy and robustness.…”
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Multi-Stage and Multi-Objective Optimization of Solar Air-Source Heat Pump Systems for High-Rise Residential Buildings in Hot-Summer and Cold-Winter Regions by Zhen Wang, Jiaxuan Wang, Chenxi Lv

“…Next, the GenOpt program and the Hooke–Jeeves algorithm are used to perform the first stage of optimization with the lowest annual cost value as the objective function. …”
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Parameter identification of photovoltaic inverter based on improved particle swarm optimization algorithm by LUO Jian, SUN Yue, JIANG Lijuan

“…The advantages of the proposed method can be obtained by comparing the synchronous identification results of the parameters， and the identification results were substituted into the simulation model.ResultsThe error of synchronous identification results of low sensitivity parameters was far beyond the acceptable range， and the error of relevant parameters identified by CGAPSO step by step was less than 1.1%， which was much higher than the accuracy of synchronous identification results.ConclusionsThe output data of the identification model based on the improved particle swarm optimization algorithm had a high agreement with the actual inverter working data，which could accurately reflect the actual working characteristics of the inverter.…”
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Optimization of Planning Layout of Urban Building Based on Improved Logit and PSO Algorithms by Yun Li, Yanping Chen, Miaoxi Zhao, Xinxin Zhai

“…Then, the evaluation model of urban building planning based on improved logit and PSO algorithm is established. …”
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Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

“…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
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Approximated Optimal Solution for Economic Manufacturing Quantity Model by Jinyuan Liu, Pengfei Jiang, Shr-Shiung Hu, Gino K. Yang

“…This study investigates the use of the bisection algorithm in inventory models to obtain an approximated optimal solution for the economic manufacturing quantity (EMQ) problem under imperfect production conditions. …”
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Ballistic Fitting Impact Point Prediction Based on Improved Crayfish Optimization Algorithm by Baolu Yang, Liangming Wang, Jian Fu

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A Novel Improved Binary Optimization Algorithm and Its Application in FS Problems by Boyuan Wu, Jia Luo

“…Secondly, a multi-population evolutionary strategy is introduced, which takes into account the diversity of individuals based on fitness values to optimize the balance between exploration and exploitation stages of the algorithm, ultimately improving the algorithm’s capability to explore the FS solution space globally. …”
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An Improved Chaos Genetic Algorithm for T-Shaped MIMO Radar Antenna Array Optimization by Xin Fu, Xianzhong Chen, Qingwen Hou, Zhengpeng Wang, Yixin Yin

“…Improved chaotic genetic algorithm optimization model is established. …”
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Research on hybrid intrusion detection based on improved Harris Hawk optimization algorithm by Pengzhen Zhou, Huifu Zhang, Wei Liang

“…The improved Harris Hawk optimization algorithm is used as a feature selection scheme to reduce the impact of redundant and noisy features on the performance of the classification model. …”
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Optimal ecological restoration strategy development based on value-cost trade-offs by Yunxuan Liu, Cui Zhang, Miaomiao Xie, Jingyi Xie

“…In addition, we searched for Pareto-optimal solutions using the nondominated sorting genetic algorithm II (NSGA-II) to balance the trade-offs between different objectives. …”
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An Improved Adaptive Simulated Annealing Particle Swarm Optimization Algorithm for ARAIM Availability by Ershen Wang, Xiaozhu Shi, Xidan Deng, Jing Gao, Wei Zhang, Huan Wang, Song Xu

“…Aiming at this problem, we proposed an adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm to redistribute integrity and continuity risks and establish a protection level optimization model. …”
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The Hub Location and Flow Assignment Problem in the Intermodal Express Network of High-Speed Railways and Highways by Xiaoting Shang, Zhenghang Wang, Xin Cheng, Xiaoyun Tian

“…Owing to the NP-hard computational complexity, an improved genetic algorithm with local search is designed by combining the genetic operators and two optimization strategies to solve the problem effectively. …”
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AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm by Rafat Alshorman, Bilal H. Abed-alguni, Yaqeen E. Alqudah

“…Finally, Dynamic Opposition-based Learning is utilized to improve the mutation capability of the AOAFS. Several malware datasets were used to compare the AOAFS to four popular Machine Learning algorithms and eight famous wrapper-based optimization algorithms. …”
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Improving Parameter Estimation of Fuel Cell Using Honey Badger Optimization Algorithm by Rolla Almodfer, Mohammed Mudhsh, Samah Alshathri, Laith Abualigah, Laith Abualigah, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Khurram Shahzad, Mohamed Issa

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A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources by Zihao Wang, Shenhua Wang, Hanwen Ni, Junyin Wang, Jun Zhang

“…Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. …”
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