LSTM-ANN-GA A HYBRID DEEP LEARNING MODEL FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPEMENT by Farouk Noumich, Abouchabaka Jaafar, Amrani Ayoub

“…Predictive maintenance is essential for ensuring the reliability of industrial equipment and minimizing maintenance costs. However, current predictive algorithms sometimes reach their limits in terms of accuracy, necessitating continuous improvement. …”
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Improved RRT-Based Obstacle-Avoidance Path Planning for Dual-Arm Robots in Complex Environments by Jing Wang, Genliang Xiong, Bowen Dang, Jianli Chen, Jixian Zhang, Hui Xie

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Anterior Cruciate Ligament Tear Detection Based on Combination of Convolutional Neural Network Enhanced by Improved Human Evolutionary Algorithm by Haibo Shen

“…This study proposes a new efficient technique for detecting tears of ACL based on the integration of a Convolutional Neural Network (CNN) and an improved version of Human Evolutionary Algorithm (IHEA). …”
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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…It reduces trial-and-error efforts and supports mix design optimization. Currently, machine learning is more adept at handling complicated datasets than experimental and traditional statistical models. …”
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Risk Assessment of Heavy Rain Disasters Using an Interpretable Random Forest Algorithm Enhanced by MAML by Yanru Fan, Yi Wang, Wenfang Xie, Bin He

“…Based on disaster system theory, we constructed a heavy rain disaster risk assessment framework from four dimensions. We improved the application of model-agnostic meta-learning (MAML) in hyperparameter optimization for the random forest (RF) algorithm, thereby developing the MAML-RF heavy rain disaster risk assessment model. …”
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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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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The present study proposes a novel dynamic prediction model for high-altitude PV efficiency, namely the GVSAO-CNN, which combines the Gravity Search Optimization Algorithm (GVSAO). …”
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Optimal Coordination of Directional Overcurrent Relays Using an Innovative Fractional-Order Derivative War Algorithm by Bakht Muhammad Khan, Abdul Wadood, Herie Park, Shahbaz Khan, Husan Ali

“…This innovative approach integrates the principles of fractional calculus (FC) into the conventional war optimization (WO) algorithm, significantly improving its optimization properties. …”
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A rapid detection method for egg quality using CARS and SSA⁃XGBoost improved by combining hyperspectral analysis by WANG Linyi, ZOU Qianying, SUN Qiang

“…Optimizing multiple hyperparameters of the XGBoost model through the Tartary Sea Salp Swarm Algorithm to improve the predictive performance of the XGBoost model. …”
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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…The hybrid algorithm's primary characteristic is its capacity to simultaneously fulfil multiple objectives, including reducing response times, enhancing resource efficiency, and decreasing operational costs. …”
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Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…Predicting the time series energy consumption data of manufacturing processes can optimize energy management efficiency and reduce maintenance costs for enterprises. …”
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Tensor RT optimized driver drowsiness detection system using edge device by Chandramohan Dhasarathan, Sambasivam Gnanasekaran, Arnab Pattanayak, Gourav Kumar, Kartik Vig, Vaibhav Narain, K.M. Deva Narayan, Sunidhi Garg

“…The proposed approach utilizes multiple models to improve and accurately detecting driver drowsiness, with the models being InceptionV3, ResNet50, VGG-16, and MobileNetV1. …”
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Multiobjective Cognitive Cooperative Jamming Decision-Making Method Based on Tabu Search-Artificial Bee Colony Algorithm by Fang Ye, Fei Che, Lipeng Gao

“…Most of the existing studies about jamming decision only pay attention to the jamming benefits, while ignoring the jamming cost. In addition, the conventional artificial bee colony algorithm takes too many iterations, and the improved ant colony (IAC) algorithm is easy to fall into the local optimal solution. …”
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Optimization configuration method of integrated energy system for reliability improvement of distribution network by SHI Mingming, MIAO Huiyu, GUO Jiahao, JIANG Yunlong, XIAO Xiaolong

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Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines. by Takuro Matsuta, Ryo Furue

“…We cast the linear partial differential equation governing the Stommel model into an optimization problem by the least-squares method and discretize the cost function in two ways: finite difference and truncated basis expansion. …”
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COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization by Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin

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A monthly runoff prediction model based on ICEEMD-L-SHADE-SRU by Ziyang Kou, Yang Yang, Zhiping Li, Xiaoshuang Fu

“…L-SHADE is employed to complete the parameter optimization of the SRU. The results showed that ICEEMD-L-SHADE-SRU achieved the best performance in runoff prediction, showing distinct improvements when compared to tested models in terms of both NSE (0.91–0.93) and QR (72%–74%). …”
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Advanced Optimization Methods for Nonlinear Backstepping Controllers for Quadrotor-Slung Load Systems by Muhammad Maaruf, Sulaiman S. Ahmad, Waleed M. Hamanah, Abdullah M. Baraean, Md Shafiul Alam, Mohammad A. Abido, Md Shafiullah

“…Then the formulated optimization problem is then solved by employing two efficient metaheuristic algorithms, the improved grey wolf optimizer (IGWO) and the whale optimization algorithm (WOA). …”
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An improved ant colony optimization strategy for dual-objective high-speed train scheduling by Hui Zhao, Jiahuan Zhang, Haixing Li, Dong Li

“…Then, an improved ant colony optimization algorithm is proposed to solve the model. …”
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Optimal Driving Torque Control Strategy for Front and Rear Independently Driven Electric Vehicles Based on Online Real-Time Model Predictive Control by Hang Yin, Chao Ma, Haifeng Wang, Zhihao Sun, Kun Yang

“…Active slip control is applied when slip rates exceed critical thresholds, while under normal conditions, torque distribution is optimized to minimize energy losses. To enable online real-time implementation, an improved sparrow search algorithm (SSA) is designed. …”
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