Dynamic Grouping Control of BESS for Remaining Useful Life Extension and Overall Energy Efficiency Improvement in Smoothing Wind Power Fluctuations by Yang Yu, Dongyang Chen, Yuwei Wu, Boxiao Wang, Yuhang Huo, Wentao Lu, Zengqiang Mi

“…Second, a model to optimize capacity allocation for three battery groups (BGs) in BESS is established considering LL and OEE, and it is solved by the designed improved beetle swarm antennae search algorithm. …”
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Robust prediction of tool-tissue interaction force using ISSA-optimized BP neural networks in robotic surgery by Yong-Li Yan, Teng Ren, Li Ding, Tiansheng Sun, Shandeng Huang

“…Methods The current proposal concerns a deep learning-based solution utilizing a backpropagation neural network (BPNN) optimized by improved sparrow search algorithm (ISSA) to predict clamp force on soft tissue. …”
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A Combined PSO-LSTM Prediction Model for Dam Deformation by HAO Ze-jia, SHI Yu-qun, CHENG Bo-chao, HE Jin-ping

“…By leveraging the long-short-term memory (LSTM) model and particle swarm optimization (PSO) algorithm from artificial intelligence technology, a combined PSO-LSTM dam deformation prediction model is established, offering a novel approach for enhancing the accuracy of dam deformation prediction. …”
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Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study by Una Kjällquist, Nikos Tsiknakis, Balazs Acs, Sara Margolin, Luisa Edman Kessler, Scarlett Levy, Maria Ekholm, Christine Lundgren, Erik Olsson, Henrik Lindman, Antonios Valachis, Johan Hartman, Theodoros Foukakis, Alexios Matikas

“…Purpose: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. …”
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Load balancing method of service cluster based on mean-variance by Xiaoan BAO, Xue WEI, Lei CHEN, Guoheng HU, Na ZHANG

“…When a large number of concurrent requests are allocated,the load scheduling mechanism is to achieve the load balancing of nodes in the network by minimizing the response time and maximizing the utilization ratio of nodes.In the load balancing algorithm based on genetic algorithm,the fitness function is designed to have an important influence on the load balancing efficiency.A service cluster load balancing method based on mean-variance was proposed to optimize the fitness function.The investment portfolio selection model mean-variance was used to minimize the response time,which was used to get the weight of each server's resource utilization,so as to obtain the optimal allocation combination.This method improves the accuracy and efficiency of the fitness function.Compared with other models in different service environment,the simulation results show that the load balancing algorithm makes the service cluster get a better balance performance in terms of node utilization and response time.…”
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Photovoltaic Module Fault Detection Technology Based on Remote Sensing Technology and Deeplabv3+ Model by Xiaowei Xu, Mingxian Liu, Yongjie Nie, Ke Wang, Wenhua Xu

“…The statistical test results showed that the improved K-means algorithm was significantly better than the traditional K-means in clustering accuracy, and its average error was only 0.008, which was much lower than the 0.035 of the traditional K-means. …”
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Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

“…This knowledge helps in identifying critical factors that significantly influence the model’s outcomes and can guide efforts to improve the accuracy and reliability of predictions. …”
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Intelligent pattern design using 3D modelling technology for urban sculpture designing by Wei Wan

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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

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Prediction of Water Quality in Agricultural Watersheds Based on VMD-GA-LSTM Model by Yuxuan Luo, Xianglan Meng, Yutong Zhai, Dongqing Zhang, Kaiping Ma

“…In order to solve the nonlinear and non-stationary characteristics of water quality data, this paper proposes a combined model based on variational modal decomposition and genetic algorithm optimization of long short-term memory networks (VMD-GA-LSTM) for agricultural watershed water quality prediction. …”
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Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks by Aida Issembayeva, Oleksandr Kuznetsov, Anargul Shaushenova, Ardak Nurpeisova, Gabit Shuitenov, Maral Ongarbayeva

“…While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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DeepDate: A deep fusion model based on whale optimization and artificial neural network for Arabian date classification. by Nour Eldeen Mahmoud Khalifa, Jiaji Wang, Mohamed Hamed N Taha, Yudong Zhang

“…<h4>Method</h4>In this paper, a deep fusion model based on whale optimization and an artificial neural network for Arabian date classification is proposed. …”
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A Review of Quantitative Characterization of Phase Interface Dynamics and Optimization of Heat Transfer Modeling in Direct Contact Heat Transfer by Mingjian Wang, Jianxin Xu, Shibo Wang, Hua Wang

“…Many scholars have focused their research on optimizing the working conditions and structure of direct contact heat transfer in order to improve heat transfer efficiency. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…In response, the automotive industry is actively engaging in new sensor technologies and innovative control and diagnostic algorithms that improve energy sustainability and reduce vehicle emissions. …”
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Enhancing Security in CPS Industry 5.0 using Lightweight MobileNetV3 with Adaptive Optimization Technique by Mohammed A. Aleisa

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Research on the Thrust Allocation Method for Straight-Line Sailing of Multiple AUVs in Tandem Connection by Jin Zhang, Shengfan Zhu, Shuai Kang

“…Second, an improved Genetic Algorithm (GA) was developed to optimize thrust values for each unit in smaller configurations. …”
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Emergency Resource Dispatch Scheme for Ice Disasters Based on Pre-Disaster Prediction and Dynamic Scheduling by Runyi Pi, Yuxuan Liu, Nuoxi Huang, Jianyu Lian, Xin Chen, Chao Yang

“…First, the fast Newman algorithm is employed to cluster communities, optimizing the preprocessing of resource scheduling and reducing scheduling costs. …”
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Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…This decreases the complexity of the model without losing essential information. Finally, a Graph Convolutional Split-Attention Network (SGCSAN) for promisingly predicting whether the stock prices are going to hit the ground and fly high again or is going to nosedive with Humboldt Squid Optimization Algorithm (HSOA) is introduced to further improve accuracy with lesser error generation. …”
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A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…Therefore, in this study, we propose the YOLOV5M-SBSD tea bud lightweight detection model to address the above issues. The Fuding white tea bud image dataset was established by collecting Fuding white tea images; then the lightweight network ShuffleNetV2 was used to replace the YOLOV5 backbone network; the up-sampling algorithm of YOLOV5 was optimized by using CARAFE modular structure, which increases the sensory field of the network while maintaining the lightweight; then BiFPN was used to achieve more efficient multi-scale feature fusion; and the introduction of the parameter-free attention SimAm to enhance the feature extraction ability of the model while not adding extra computation. …”
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Using Cuckoo Search Algorithm to Predict Corporate Financial Risks and Alleviate Economic Uncertainty by Muqiao Cai

“…Advanced forecasting models must be combined with robust optimization methods to address these challenges effectively. …”
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