Collaborative Planning for Distribution Network and PV-ESS in the Marketization Environment by Ping RAO, Yue XIANG, Haotian YAO, Youbo LIU, Junyong LIU

“…In addition, the timing operation results of the distribution network in typical scenes were obtained in the operation layer using the benefit coupling model and energy storage operation strategy. The double-layer improved particle swarm optimization algorithm was applied to run the model. …”
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Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…The first scenario used the original dataset, the second used a merged version of the dataset, and the last scenario used a hierarchical architecture model. Additionally, a custom ranking algorithm was designed to identify the most suitable recipients. …”
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Research on action matching of skeletal point coordinates and sports teaching application based on Open-pose by Shunmin Su

“…Experimental results show that the loss rate of the skeletal point coordinate action matching method proposed in this paper is 12.4 %, and the Rank-n recognition rate can reach up to 95.2 %, which has higher accuracy, and the application in physical education is conducive to improving the completion of the course tasks, promoting the optimization of the education model, and has good application value.…”
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An Optimised Method for Fetching and Transforming Survey Data based on SQL and R Programming Language by Hasan et al.

“…This method demonstrated improved accuracy of data collected, reduced data processing time and arranged data to the willing model.…”
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Real-time torque distribution simulation of parallel hybrid vehicle engine by Jing Wang

“…Validation employed the Gamma Technologies Suite simulation platform and the Next Generation Simulation dataset, with benchmark comparisons against Equivalent Consumption Minimization Strategy, Fuzzy Logic Control, and Thermostat Strategy models.ResultsThe optimized Proximal Policy Optimization algorithm achieved 93.2% accuracy and 1.0% loss rate upon convergence, with an average feedback time of 32 milliseconds. …”
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Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

“…Specifically, in order to improve optimization efficiency, greedy bilateral smoothing is employed to model low rank backgrounds, resulting in a significant improvement in the efficiency of the detection algorithm. …”
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Perimeter Degree Technique for the Reduction of Routing Congestion during Placement in Physical Design of VLSI Circuits by Kuruva Lakshmanna, Fahimuddin Shaik, Vinit Kumar Gunjan, Ninni Singh, Gautam Kumar, R. Mahammad Shafi

“…Consequently, in conjunction with the optimized floorplan data, the optimized model created by the Improved Harmonic Search Optimization algorithm undergoes testing and investigation in order to estimate the amount of congestion that occurs during the routing process in VLSI circuit design and to minimize the amount of congestion that occurs.…”
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Multi-Objective Technology-Based Approach to Home Healthcare Routing Problem Considering Sustainability Aspects by Ahmed Adnan Zaid, Ahmed R. Asaad, Mohammed Othman, Ahmad Haj Mohammad

“…<i>Methods</i>: The model was solved using a metaheuristic algorithm approach via the Ant Colony Optimization algorithm and the Non-Dominated Sorting technique due to the ability of such a combination to work out with dynamic models with uncertainties and multi-objectives. …”
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Fault diagnosis method of timing signal based on Nadam-TimeGAN and XGBoost by HEI Xinhong, GAO Miao, ZHANG Kuan, FEI Rong, QIU Yuan, JI Wenjiang

“…The Nadam optimization algorithm was used to optimize the components of the TimeGAN model, that was, the Nadam-TimeGAN model was constructed for data expansion. …”
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基于遗传算法的可调空间机构RRSS的轨迹优化综合 by 安帅伟, 林光春, 聂志萍, 吴伟

“…The method of track optimal synthesis for the adjustable spatial RRSS mechanism for multi-tasks based on Genetic Algorithm is proposed.The mechanism optimization model is established by taking the minimum of square of the error between the actual trajectories and beforehand ascertainable trajectories as the goal function.And the global optimization solution is gained by the Genetic Algorithms.In order to improve the evolutionary speed and accuracy of solutions effectively,a method that can adaptively adjust mutation rate and value according to fitness of individual is used,at the last,a numeric example is given to illustrate the method.…”
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Finding the Shortest Path with Vertex Constraint over Large Graphs by Yajun Yang, Zhongfei Li, Xin Wang, Qinghua Hu

“…In this paper, we first propose a novel exact heuristic algorithm in best-first search way and then give two optimizing techniques to improve efficiency. …”
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A Long-Term Shared Autonomous Vehicle System Design Problem considering Relocation and Pricing by Jingjing Tian, Hongfei Jia, Guanfeng Wang, Yu Lin, Ruiyi Wu, Ao Lv

“…Then, we integrate the Particle Swarm Optimization (PSO) algorithm with the optimization solver Gurobi to address the complex problem. …”
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Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network by Zhichao ZHOU, Yi FENG, Xiaohan XIA, Yuyao FENG, Chao CAI, Jiahui QIU, Lihui YANG, Yunxiao WU

“…The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services.The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications.The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research.Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location.By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources.Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined.Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results.Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented.…”
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Flight Endurance Increasing Technology of New Energy UAV Based on a Strut-Braced Wing by Li Liu, Wencan Bai, Dun Yang

“…Surrogate model technology and multiobjective genetic algorithm are used to optimize the SBW configuration. …”
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Soft Measurement of Wastewater Treatment System Based on PSOGA-WNN by LIU Yuhui, MAI Wenjie, LI Xiaoyong, ZHAO Yinzhong, HE Xinzhong, HUANG Mingzhi

“…To accurately predict the SS_eff (effluent SS) content and COD_eff (effluent COD) concentration in water quality parameters and further improve the water quality early warning mechanism,this paper proposes the PSOGA-WNN soft measurement model of paper wastewater effluent quality to obtain the main water quality technical parameters,COD_inf (influent COD),Q (influent flow),pH (influent pH),SS_inf (influent SS),T (influent temperature),DO (influent dissolved oxygen),COD_eff,and SS_eff, for predicting the quality of wastewater from the wastewater treatment plant.Among them,the prediction results of PSOGA-WNN are compared with the neural networks of PSO-WNN,GA-WNN,and PSOGA-BP.The results show that the PSOGA-WNN neural network has the highest prediction accuracy,which indicates that the PSOGA hybrid parameter optimization algorithm based on the genetic algorithm and particle swarm algorithm has obvious superiority in optimizing the prediction accuracy of the model.The WNN neural network has certain advantages over BP neural network in terms of fitting degree as well as error accuracy and is an effective means of simulation prediction.…”
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Consumer-Centered Collaborative Governance of Regional Business Environment by Tingting Xiang, Hongzhi Lin

“…This paper proposes a bi-level programming model based on consumer welfare, with the upper-level model focusing on optimizing the government’s investment allocation strategy to maximize consumer welfare, and the lower-level model addressing the spatial price equilibrium problem after improving the business environment. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  …”
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Data-Driven Customer Retention Strategies in E-Commerce: A Fuzzy Z-Number Approach by Siyin Hu, An Chen

“…For the purpose of evaluating customer churn, we use the Support Vector Machine (SVM) model. In order to improve the performance of the SVM, we tune its parameters using the Coyote Optimization Algorithm (COA). …”
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Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…Meanwhile, the particle swarm optimization (PSO) algorithm is used to solve the multi-objective scheduling problem to achieve the global objectives of energy conservation, cost reduction, and comfort optimization. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…The method first adapts the parameters of the variational modal noise reduction algorithm using an improved sparrow optimization algorithm, and then reconstructs the original vibration signal with noise reduction. …”
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