IMPROVE OF UNCERTAIN MICROSATELLITE MAGNETIC CLEANLINESS BASED ON MAGNETIC FIELD SPATIAL HARMONICS COMPENSATION by Б.І. Кузнецов, Т.Б. Нікітіна, І.В. Бовдуй, К.В. Чуніхін, В.В. Коломієць, Б.Б. Кобилянський

“…Both vector game solution calculated based on particles multi-swarm optimization (PMSO) algorithms from Pareto optimal solutions taking into account binary preference relations. …”
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Image cluster algorithm of hybrid encoding method by Chun-hui ZHAO, Xue-yuan LI, Ying CUI

“…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning by Mohammad D. Alahmadi, Ahmed S. Alzahrani

“…The increasing presence of heavy connected vehicles (HCVs) in urban traffic necessitates optimized signal-control strategies to improve efficiency. …”
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IMPROVEMENT OF PASSENGER SERVICE PROCESSES OF DEPARTING FLIGHT BASED ON PROJECT MANAGEMENT METHODS by S. A. Kropiventseva

“…The article considers the formalization of the service technology of departing passengers into network model, which is a good basis for improving the service technology, monitoring the performance that determines the process duration and service optimization in cost and resources. …”
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Simultaneous Energy Optimization of Heating Systems by Multi-Zone Predictive Control—Application to a Residential Building by Rina Bitar, Nicolas Youssef, Julien Chamoin, Fadi Hage Chehade, Didier Defer

“…The research methodology uses dynamic thermal simulation, parallel predictive models based on multiple linear regressions, and a multi-objective non-dominated sorting genetic algorithm II (NSGA-II) for the optimization process, which evaluates various generated heating strategies. …”
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A novel approach to intrusion detection system using hybrid flower pollination and cheetah optimization algorithm by Deepshikha Kumari, Prashant Pranav, Abhinav Sinha, Sandip Dutta

“…Abstract The study aims to address critical challenges in network security, particularly the limitations of traditional intrusion detection systems (IDS) in terms of adaptability, detection precision, and high false positive rates in dynamic network environments. A novel hybrid IDS model integrating the Flower Pollination Algorithm (FPA), Cheetah Optimization Algorithm (COA), and Artificial Neural Networks (ANN) is proposed to enhance detection accuracy, reduce false positives, and optimize feature selection, anomaly detection, and rule adaptation. …”
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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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Efficiency Improvement of Wireless Charging System Based on Active Power Source in Receiver by Bingkun Shi, Fuyuan Yang, Shidong Wang, Minggao Ouyang

“…A novel current decoupling algorithm is used to analyze the efficiency of the new configuration, and a simulation model is established to validate the theoretical result and to explain the mechanism of efficiency improvement. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. The core of the research lies in enhancing the feature extraction capability of the model, optimizing the feature expression of the model by introducing the CBAM attention mechanism, and improving the original structure of the neck component. …”
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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

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Application of Improved WOA in Hammerstein Parameter Resolution Problems under Advanced Mathematical Theory by Lu Zhao, Jiangjun Liu, Yuan Li

“…In response to the fact that whale optimization algorithms are prone to falling into local optima and the identification of important Hammerstein models ignores the issue of noise outliers in actual industrial environments, this study improves the whale algorithm and constructs a Hammerstein model identification strategy for nonlinear systems under heavy-tailed noise using the improved whale algorithm. …”
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Improved GOA-based fuzzy PI speed control of PMSM with predictive current regulation. by Taochang Li, Ang Li, Limin Hou

“…Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima. …”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

“…Moreover, we introduce a cross-model method with a genetic algorithm to compute the optimal weights for the RBF-NN model. …”
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Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…The RF_WOA_DBO hybrid model achieved an accuracy of 98.29%, representing a 4.28% improvement over the baseline RF model. …”
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Water Supply Scheduling for Cross-basin Reservoir Groups Based on Improved Scheduling Diagram by ZHAO Siqi, XU Wei, CHEN Si, WANG Sufan, YANG Yi

“…To exploit the scheduling potential of cross-basin reservoir groups by employing runoff information,this paper proposes an improved reservoir scheduling diagram to retain simplicity and intuitiveness.Taking the Xiajiankou,Fengyan,and Nanpeng reservoirs in Banan District of Chongqing as an example,it adopts the POA algorithm to build a joint scheduling model of water diversion and water supply for the cross-basin reservoir groups by a simulation-optimization approach.Meanwhile,three scenarios of the current situation scheduling,optimized scheduling with conventional scheduling diagrams,and optimized scheduling with improved scheduling diagrams are set up to evaluate the water diversion and supply performance of reservoirs and analyze the influence of uncertainty runoff information on the scheduling performance.The results are as follows:① The improved scheduling diagram performs best in the long series scheduling,and it can increase the annual average water supply of the reservoir group by 6.87% and reduce the abandoned water by 87.58% compared with the current situation scheduling;② In a dry year,the method can reduce 486.3×10⁴ m³ of water shortage and increase 477.6×10⁴ m³ of water for power generation based on the current situation scheduling;③ When considering the runoff information uncertainty,the water supply of the improved scheduling diagram is 3.37% lower than the ideal case but is still 5.96% more than the conventional optimization.The results are conducive to making scientific decisions and improving the water supply effect.…”
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Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller by Vineet Kumar, Vineet Kumar, Ark Dev

“…The proposed controller is benchmarked against conventional PID, fractional-order PIλDF, and MPC schemes optimized via Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). …”
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Vessel Traffic Flow Prediction in Port Waterways Based on POA-CNN-BiGRU Model by Yumiao Chang, Jianwen Ma, Long Sun, Zeqiu Ma, Yue Zhou

“…Aiming at the stage characteristics of vessel traffic in port waterways in time sequence, which leads to complexity of data in the prediction process and difficulty in adjusting the model parameters, a convolutional neural network (CNN) based on the optimization of the pelican algorithm (POA) and the combination of bi-directional gated recurrent units (BiGRUs) is proposed as a prediction model, and the POA algorithm is used to search for optimized hyper-parameters, and then the iterative optimization of the optimal parameter combinations is input into the best combination of iteratively found parameters, which is input into the CNN-BiGRU model structure for training and prediction. …”
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Artificial intelligence for smart irrigation: Reducing water consumption and improving agricultural output by Arlanova A. A., Hojamkuliyeva B. A., Babanazarov N. Sh., Arlanov M. S.

“…Existing approaches to using artificial intelligence in agricultural technologies for predicting water needs and regulating irrigation are examined. A mathematical model based on machine learning algorithms is developed to predict the optimal water volume required for irrigation of agricultural crops. …”
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Application of HHO-CNN-LSTM-based CMAQ correction model in air quality forecasting in Shanghai by ZHENG Xinnan, LIN Kaiyan, WANG Zijing, SONG Yuanbo, SHI Yang, LU Hanyue, ZHANG Yalei, SHEN Zheng*

“…Accordingly, a correction model, which combines convolutional neural network (CNN) and long-short term memory neural network (LSTM) and optimized by harris hawks optimization algorithm (HHO) was established to enhance the accuracy of CMAQ model's prediction results for six air pollutants (SO_2, NO_2, PM_10, PM_2.5, O_3 and CO). …”
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A Crash Severity Prediction Method Based on Improved Neural Network and Factor Analysis by Chen Zhang, Jie He, Yinhai Wang, Xintong Yan, Changjian Zhang, Yikai Chen, Ziyang Liu, Bojian Zhou

“…The results showed that although the algorithms produced almost the same accuracy in their predictions, a backpropagation method combined with a nonlinear inertial weight setting in PSO produced fast global and accurate local optimal searching, thereby demonstrating a better understanding of the entire model explanation, which could best fit the model, and at last, the factor analysis showed that non-road-related factors, particularly vehicle-related factors, are more important than road-related variables. …”
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