Improved Asynchronous Federated Learning for Data Injection Pollution by Aiyou Li, Huoyou Li, Yanfang Liu, Guoli Ji

“…In view of the problems of data pollution, incomplete feature extraction, and poor multi-network parameter sharing and transmission under the federated learning framework of deep learning, this article proposes an improved asynchronous federated learning algorithm of multi-model fusion based on data injection pollution. …”
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Risk assessment of corn borer based on feature optimization and weighted spatial clustering: a case study in Shandong Province, China by Yanan Zuo, Min Ji, Jiutao Yang, Zhenjin Li, Jing Wang

“…Addressing the prevalent issue of class imbalance in pest datasets, a feature optimization model using Borderline-SMOTE to improve the Genetic Algorithm-Random Forest (GA-RF) was constructed, combined with Pearson correlation coefficient to jointly obtain a subset of features that affect corn borer. …”
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ISOA‐DBN: A New Data‐Driven Method for Studying the Operating Characteristics of Air Conditioners by Mengran Zhou, Qiqi Zhang, Feng Hu, Ling Wang, Guangyao Zhou, Weile Kong, Changzhen Wu, Enhan Cui

“…We aim at solving the problems of scarcity, single type, low accuracy and difficult construction of high‐quality data sets available for air conditioning operation characteristic models at present. This paper proposes a construction method of air conditioning operation characteristic model based on an improved seagull optimization algorithm to optimize deep belief network (ISOA‐DBN). …”
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Research on Ultimate Bearing Capacity of Angular Contact Ball Bearings Considering Misalignment Angles by Wang Huijie, Qiu Ming, Li Junxing, Liu Zhiwei, Yang Chuanmeng

“…By improving the algorithm, the number of equations and the difficulty of solving the model are reduced. …”
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Optimization method of obstacle avoidance path for dual-arm cooperative robot based on machine vision by Jing Li

“…An improved bat algorithm is employed to optimize the obstacle avoidance path of the dual-arm cooperative robot, ultimately yielding the optimal path. …”
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Two-Layer Optimal Scheduling and Economic Analysis of Composite Energy Storage with Thermal Power Deep Regulation Considering Uncertainty of Source and Load by Chao Xing, Jiajie Xiao, Xinze Xi, Jingtao Li, Peiqiang Li, Shipeng Zhang

“…Secondly, based on the peaking characteristics and operating costs of composite energy storage, a two-layer optimal scheduling model of energy storage is constructed. The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. …”
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Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model by Elhoucine Ouassam, Yassine Dabachine, Nabil Hmina, Belaid Bouikhalene

“… The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. …”
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Bi-Objective Optimization for Joint Time-Invariant Allocation of Berths and Quay Cranes by Xiaomei Zhang, Ziang Liu, Jialiang Zhang, Yuhang Zeng, Chuannian Fan

“…Given that BACASP is an NP-hard problem, an improved multi-objective cuckoo search (IMOCS) algorithm is proposed to solve this problem, in which an elite-guided tangent flight strategy is presented to speed up the convergence for making up the lack of random search direction of the traditional cuckoo search algorithm; and an information-enhanced abandonment strategy is put forward to increase the possibility of escaping from local optima. …”
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Optimization Strategy of Microgrid Hierarchical Scheduling Considering Electric Vehicles User Satisfaction Degree by Huiqun YU, Shen YIN, Hao ZHANG, Shanshan SHI, Daogang PENG, Guoshun CAI

“…Renewable energy is used to support the load of the microgrid in the source storage layer, and the excess part is absorbed by the dispatchable electric vehicle, which makes the comprehensive cost of the microgrid minimized. The improved ant lion algorithm is used to solve the model of the source storage layer. …”
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Enhanced anomaly network intrusion detection using an improved snow ablation optimizer with dimensionality reduction and hybrid deep learning model by Fatimah Alhayan, Asma Alshuhail, Ahmed Omer Ahmed Ismail, Othman Alrusaini, Sultan Alahmari, Abdulsamad Ebrahim Yahya, Sami Saad Albouq, Mutasim Al Sadig

“…Finally, the improved Snow Ablation Optimizer (ISAO) model optimally tunes the hyperparameters of the LSTM–AE model, leading to enhanced classification performance. …”
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Research on a Density-Based Clustering Method for Eliminating Inter-Frame Feature Mismatches in Visual SLAM Under Dynamic Scenes by Zhiyong Yang, Kun Zhao, Shengze Yang, Yuhong Xiong, Changjin Zhang, Lielei Deng, Daode Zhang

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Artificial neural network-driven approaches to improved forecasting of disability care expenditures in an aging Kingdom of Saudi Arabia population by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Furthermore, the bidirectional variational autoencoder with the self-attention module (BiVAE‐SAM) model forecasts disability care expenses. Finally, the enriched coati osprey algorithm (ECOA)-based hyperparameter selection process is performed to optimize the prediction results of the BiVAE‐SAM method. …”
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Heuristic XAI: AIME and HMM Integration Improved-Feature-Importance Assessment Through Heuristics by Takafumi Nakanishi, Ponlawat Chophuk, Krisana Chinnasarn

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Application of Improved Image Processing Technology in New Media Short Video Quality Improvement in Film and Television Postproduction by Yi Wang

“…In this paper, a convolutional neural network combined with a nonlinear activation function is used to establish an improved image processing technology model to efficiently extract image features. …”
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An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures by Xue-Yang Pei, Hai-Bin Huang, Peng Cao

“…Nonstationary and nonlinear variations in modal frequencies, commonly induced by environmental changes, tend to overshadow the effects caused by structural damage. An improved Gaussian mixture model (GMM) is proposed in this paper to normalize nonlinear and nonstationary frequency data, enabling effective structural damage detection under variable environmental conditions. …”
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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system by Ivan V. Stepanyan, Safa A. Hameed

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Electromyography-based gesture recognition for quadriplegic users using hidden Markov model with improved particle swarm optimization by Xanno K Sigalingging, Alrezza Pradanta Bagus Budiarsa, Jenq-Shiou Leu, Jun-ichi Takada

“…The signals are then processed using a novel algorithm that employs hidden Markov model and improved particle swarm optimization to classify the gesture. …”
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Improving T2D machine learning-based prediction accuracy with SNPs and younger age by Cynthia AL Hageh, Andreas Henschel, Hao Zhou, Jorge Zubelli, Moni Nader, Stephanie Chacar, Nantia Iakovidou, Haralampos Hatzikirou, Antoine Abchee, Siobhán O’Sullivan, Pierre A. Zalloua

“…Results: The inclusion of genomic data modestly improved model performance across all algorithms in the discovery dataset. …”
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An Optimized Method for Solving the Green Permutation Flow Shop Scheduling Problem Using a Combination of Deep Reinforcement Learning and Improved Genetic Algorithm by Yongxin Lu, Yiping Yuan, Jiarula Yasenjiang, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…It introduces a novel hybrid approach that combines end-to-end deep reinforcement learning with an improved genetic algorithm. Firstly, the PFSP is modeled using an end-to-end deep reinforcement learning (DRL) approach, named PFSP_NET, which is designed based on the characteristics of the PFSP, with the actor–critic algorithm employed to train the model. …”
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