Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nong... by Yuxiang Wang, Zhangwei Chen, Hongfei Zu, Xiang Zhang, Chentao Mao, Zhirong Wang

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Simplifying Multiproject Scheduling Problem Based on Design Structure Matrix and Its Solution by an Improved aiNet Algorithm by Chunhua Ju, Tinggui Chen

“…In this paper, design structure matrix (DSM) and an improved artificial immune network algorithm (aiNet) are developed to solve a multi-mode resource-constrained scheduling problem. …”
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Optimization of New Energy Vehicle Industry Structure Based on Optimization Link Prediction Similarity Algorithm and CGE by Zhenjun Xie

“…In light of the growing global concerns over energy and climate change, new energy vehicles are confronted with both opportunities and challenges posed by industrial structural transformation. To foster the optimization of the new energy vehicle industry structure while considering environmental impact, this paper first uses an improved link prediction algorithm to construct an industrial structure optimization model. …”
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Research on UAV aerial imagery detection algorithm for Mining-Induced surface cracks based on improved YOLOv10 by Jiayong An, Siyuan Dong, Xuanli Wang, Chenlei Li, Wenpei Zhao

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Automatic Generation Technology of Safety Measures for Digital Substation Based on Improved Support Vector Machine by Yabing YAN, Xu CHU, Haolong XIAO, Wenwu LIANG, Hui LI, Zhenxing XIA

“…Firstly, construct a secondary circuit model and equipment model based on adjacency matrix, and further integrate the secondary security measure rule library to form a sample dataset; Secondly, support vector machines were used to classify secondary security measures, and bacterial foraging algorithms were introduced to optimize penalty factors and kernel parameters, effectively improving the training effectiveness of the automatic generation model for security measures; Finally, the effectiveness of the proposed method was verified through numerical examples.…”
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Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…The study concludes that feature selection and hyperparameter optimization significantly improve model accuracy and computational efficiency, offering a robust framework for air quality forecasting.…”
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Using multiple machine learning algorithms to optimize the water quality index model and their applicability by Fei Ding, Shilong Hao, Wenjie Zhang, Mingcen Jiang, Liangyao Chen, Haobin Yuan, Nan Wang, Wenpan Li, Xin Xie

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Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model by Hewu Kuang

“…The genetic algorithm is improved by immune cloning algorithm, and the CGA-BP neural network model is established to obtain the global optimal solution. …”
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Heuristic Optimization-Assisted Dilated Convolution Neural Network With Gated Recurrent Unit for Channel Estimation in NOMA-OFDM System by Vijayakumar Kondepogu, Budhaditya Bhattacharyya

“…The loss functions in the model are optimized by using the Improved Pelican Optimization Algorithm (IPOA). …”
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SCSO: snake optimization with sine-cosine algorithm for parameter extraction of solar photovoltaic models by Qingrui Li, Yongquan Zhou, Qifang Luo

“…The proposed algorithm incorporates three key improvements: (1) integration of the Sine–Cosine Algorithm to enhance the bio-inspired Snake Optimization, balancing exploration and exploitation; (2)The parameters C 1 and C 2 are adaptively adjusted, and the Newton–Raphson method is introduced to accelerate the algorithm’s convergence speed which accelerates convergence; and (3) application of a lens imaging reverse learning strategy to improve exploration capabilities and population diversity, preventing the algorithm from becoming trapped in local optima. …”
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Optimization of Torque Models for Radial Meshing Nutation Magnetic Gears Based on the Genetic Algorithm by Lou Meiyan, Yao Ligang, Guo Chenxian

“…The genetic algorithm is used to optimize the structural parameters of the nutation magnetic gear, and the effectiveness of the optimization results is verified. …”
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Research on the Development Model of Rural Tourism Based on Multiobjective Planning and Intelligent Optimization Algorithm by Lu Yang, Xiaoying Dong

“…In order to improve the effect of rural tourism development, this study combines multiobjective planning and intelligent optimization algorithms to analyze the development mode of rural tourism and further deals with the problem of multisensor target tracking under unknown input interference conditions by designing a tourism network consensus algorithm. …”
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Deep learning for algorithmic trading: A systematic review of predictive models and optimization strategies by MD Shahriar Mahmud Bhuiyan, MD AL Rafi, Gourab Nicholas Rodrigues, MD Nazmul Hossain Mir, Adit Ishraq, M.F. Mridha, Jungpil Shin

“…This systematic literature review explores recent advancements in the application of DL algorithms to algorithmic trading with a focus on optimizing financial market predictions. …”
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Territorial Space Optimization Method Based on Multi-Objective Genetic Algorithm and FLUS Model by Lin Ge

“…The innovation of the research lies in the optimization of the multi-objective genetic algorithm by improving the crossover and mutation process of genetic operators, enhancing the adaptability of the algorithm in dynamic environments, and improving the prediction accuracy of the spatial quantity structure of the national territory. …”
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Pedestrian Re-Recognition Algorithm Based on Optimization Deep Learning-Sequence Memory Model by Feng-Ping An

“…Based on the above explanation, this paper proposes a pedestrian re-recognition algorithm based on an optimized LSTM deep learning-sequence memory learning model. …”
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Research on the optimization of mortar mix proportion based on neural network models and genetic algorithm by Chunyu Jiang

“…The genetic algorithm is then applied to optimize the model’s predictions, yielding the optimal mix design. …”
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Optimization Design Method of Pipe-Insulating Joints Based on Surrogate Model and Genetic Algorithm by Chen Guo, Zheng Yang, Jianbo Dong, Yanchao Yue, Linjun Tian, Ping Ma

“…This improves the computational efficiency of the optimization algorithm by establishing a surrogate model, which can be used to optimize the dimensions of insulation joints.…”
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Optimization of rotor-side controller parameters in doubly fed induction generators based on an improved NSGA-II. by Yanling Lv, Xiang Zhao, Zexin Mou

“…In particular, a multiobjective optimization framework based on an improved nondominated sorting genetic algorithm II (NSGA-II) is proposed by establishing a dynamic model of the rotor-side converter and investigating the operational dynamics of proportional-integral-derivative controllers under voltage transients. …”
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Spatial feature recognition and layout method based on improved CenterNet and LSTM frameworks by Yuxuan Gu, Fengyu Liu, Xiaodi Yi, Lewei Yang, Yunshu Wang

“…Consequently, this study introduces an advanced spatial feature recognition and layout methodology employing enhanced CenterNet and LSTM (Long Short-Term Memory) frameworks, which is bifurcated into two major components—first, HCenterNet-based feature recognition enhances feature extraction through an attention mechanism and feature fusion technology, refining the identification of small targets within complex background areas; second, a GA-BiLSTM (Genetic Algorithm - Bidirectional LSTM)-based spatial layout model uses a bidirectional LSTM network optimized with a genetic algorithm (GA), aimed at fine-tuning the network parameters to yield more accurate spatial layouts. …”
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Optimization model of electricity metering management based on MOPSO by Sheng Li, Xiaodan Zhou

“…Abstract In response to the difficulty of balancing economy and accuracy in traditional energy metering management methods, an improved particle swarm optimization model is designed to optimize energy metering management based on multi-objective particle swarm optimization, thereby achieving optimal resource allocation and maximizing management efficiency. …”
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