Identification of polynomial models of static load characteristics based on passive experiment results by N. L. Batseva, A. K. Zhuykov

“…In the paper, the technique based on the initial identification of the linear model, defined by EM-algorithm, and continued by the Lagrange multiplier method optimization with iterations by the Newton method is suggested.Results and discussion. …”
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A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…The Friedman test was utilized to rank the performance of the various algorithms, revealing the Growth Optimizer as the top performer across all the considered models. …”
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Optimizing machine learning algorithms for diabetes data: A metaheuristic approach to balancing and tuning classifiers parameters by Hauwau Abdulrahman Aliyu, Ibrahim Olawale Muritala, Habeeb Bello-Salau, Salisu Mohammed, Adeiza James Onumanyi, Ore-Ofe Ajayi

“…Diabetes mellitus poses a global health concern, prompting the development of machine learning algorithms designed to construct a model for the accurate classification of patients, enabling precise diagnoses and early-stage treatment. …”
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Data-Driven Robust Optimization for Solving the Heterogeneous Vehicle Routing Problem with Customer Demand Uncertainty by Jingling Zhang, Mengfan Yu, Qinbing Feng, Longlong Leng, Yanwei Zhao

“…Through test experiments, it is proved that the robust optimization model can effectively reduce the number of customers affected by the uncertainty, greatly improve customer satisfaction, and effectively reduce total cost and demonstrate that the improved algorithm also exhibits good performance.…”
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PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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An optimized informer model design for electric vehicle SOC prediction. by Xin Xie, Feng Huang, Yefeng Long, Youyuan Peng, Wenjuan Zhou

“…Therefore, based on the health assessment algorithm, a new optimized Informer model is proposed to predict SOC. …”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…Currently, more and more intrusion detection systems based on machine learning and deep learning are being applied to SDN, but most have drawbacks such as complex models and low detection accuracy. This paper proposes an enhanced spider wasp optimizer (ESWO) algorithm for feature dimensionality reduction of intrusion detection datasets and constructs a new intrusion detection model (IDM), namely ESWO-IDM, for SDN. …”
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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

“…The model employs a random forest algorithm integrated with a multi-task learning strategy and utilizes a particle swarm optimization (PSO) algorithm to optimize fracturing parameters. …”
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Multi-Time-Scale Layered Energy Management Strategy for Integrated Production, Storage, and Supply Hydrogen Refueling Stations Based on Flexible Hydrogen Load Characteristics of Po... by Zhuoyu Jiang, Rujie Liu, Weiwei Guan, Lei Xiong, Changli Shi, Jingyuan Yin

“…Compared with traditional optimization algorithms, it can effectively improve the ability to search for the optimal solution. …”
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Adaptive k-means clustering algorithm based on grid and domain centroid weight by Wei CAI, Guangyu SUN, Fei YANG, Bo YAO, Chuanxian LI

“…Furthermore, when the clustering accuracy exceeded 99％ compared to the k-means algorithm, the computational efficiency was significantly improved. …”
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Intelligent bulk cargo terminal scheduling based on a novel chaotic-optimal thermodynamic evolutionary algorithm by Shida Liu, Qingsheng Liu, Li Wang, Xianlong Chen

“…The proposed method is adept at achieving multiobjective optimization, simultaneously improving the service level and reducing costs for bulk cargo terminals, which in turn boosts their competitiveness. …”
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Optimal Placement of Leakage Sensors in Urban Gas Networks Based on an Ant Colony Algorithm and System Clustering by Zhewen Sui, Xiaobing Yuan, Baoping Cai, Fangqi Ye, Qingqing Duan, Zhiqiang Zhao, Xiaoyan Shao, Xin Zhou, Zhiming Hu

“…In urban gas network leakage monitoring, the optimized placement of sensors plays a pivotal role in ensuring public safety and minimizing system maintenance costs. …”
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Topology Optimization of the Network with Renewable Energy Sources Generation Based on a Modified Adapted Genetic Algorithm by A. M. Bramm, A. I. Khalyasmaa, S. A. Eroshenko, P. V. Matrenin, N. A. Papkova, D. A. Sekatski

“…The algorithm can be used in conjunction with renewable energy sources generation forecasting systems for the day ahead when planning the operating modes of power units in order to minimize the costs of covering electricity losses and improve the quality of electricity supplied.…”
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Volute Optimization Based on Self-Adaption Kriging Surrogate Model by Fannian Meng, Ziqi Zhang, Liangwen Wang

“…Optimizing the volute performance can effectively improve the efficiency of a centrifugal fan by changing the volute geometric parameter, so the self-adaption Kriging surrogate model is used to optimize the volute geometric parameter. …”
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Locality-guided based optimization method for bounded model checker by Shun WANG, Ye DU, Zhen HAN, Jiqiang LIU

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Optimizing Virtual Power Plant Performance through Three-Phase Power Flow Analysis and TCAS Algorithm by Meisam Azimi, Mehdi Foroughi, Mohammad Hadi Foroughi, Moein Moeini-Aghtaie, Hossein Yousefi, Mohammad Behzad Hadi

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Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm by Fen Yang

“…The results show that the big data integration system based on big data and dynamic decision tree algorithm has high adaptability. Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. …”
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An intelligent stochastic optimization approach for air cargo order allocation under carbon emission constraints. by Zhenzhong Zhang, Ling Zhang, Deqiang Fu, Weichun Li

“…The method finds the optimal solution through an improved adaptive large-scale neighborhood search algorithm and uses a scenario generation technique to generate the scenarios required for evaluating candidate solutions to the high-dimensional stochastic optimization problem. …”
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Intelligent interference decision algorithm with prior knowledge embedded LSTM-PPO model by ZHANG Jingke, YANG Kai, LI Chao, WANG Hongyan

“…Focusing on the issues of low efficiency and effectiveness in decision-making as well as the instability of traditional reinforcement learning model-based multi-function radar (MFR) jamming decision algorithms, a prior knowledge embedded long short-term memory (LSTM) network-proximal policy optimization (PPO) model based intelligent interference decision algorithm was developed. …”
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Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
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