Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…Meanwhile, the particle swarm optimization (PSO) algorithm is used to solve the multi-objective scheduling problem to achieve the global objectives of energy conservation, cost reduction, and comfort optimization. …”
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Inverse Kinematics of a 7-Degree-of-Freedom Robotic Arm Based on Deep Reinforcement Learning and Damped Least Squares by Shusheng Yu, Gongquan Tan

“…In this paper, we propose a novel solution to the inverse kinematics problem by combining Proximal Policy Optimization (PPO) with the Damped Least Squares (DLS) method, forming the Multistep PPO-DLS Inverse Kinematics (MPDIK) algorithm. …”
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An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development by Krishnaprasath Vellimalaipattinam Thiruvenkatasamy, Hayder M. A. Ghanimi, Sudhakar Sengan, Meshal Ghalib Alharbi

“…Central to this model is the proposed Quantum Neural Network + Bayesian Optimization (QNN + BO), a practiced algorithm that, when combined with methods like the Elliptic Curve Cryptography (ECC) and Coyote Optimization Algorithm (COA), guarantees secure data flow, processing, and storage. …”
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Pickup and delivery planning for the crowdsourced freight delivery routing problem. by Jingxian Zhang

“…To solve this combinatorial optimization problem, we propose an improved partheno genetic algorithm (IPGA) and a simulated annealing algorithm (SA). …”
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Microservice selection approach for mobile users in edge computing environment by ZHAO Shuxu, JIANG Kaijun, WANG Xiaolong

“…Furthermore, a microservice selection algorithm was proposed based on the cloud-edge speedup model and a dynamic cloud-edge migration strategy to handle cross-domain migration under user mobility. …”
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Short-Term Wind Power Prediction Based on MVMD-AVOA-CNN-LSTM-AM by Xiqing Zang, Zehua Wang, Shixu Zhang, Mingsong Bai

“…For this reason, this paper proposes a combined prediction model based on the Pearson correlation coefficient method, multivariate variational mode decomposition (MVMD), African vultures optimization algorithm (AVOA) for leader–follower patterns, convolutional neural network (CNN), long short-term memory (LSTM), and attention mechanism (AM). …”
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Research and application of Gaussian coupled control bistable stochastic resonance system with independent parameter regulation by Tiantian Hou, Shangbin Jiao, Yi Wang, Nianlong Song, Jianghua Li, Wenchuan Cui

“…This optimization approach leverages the algorithm’s ability to enhance population diversity and improve convergence accuracy, thereby optimizing the system’s performance. …”
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Video Recognition of Government Community Management Cases Based on Partial Differential Equation Method by Yumeng Sun

“…Based on this, this paper improves the traditional partial differential equation algorithm of image recognition, selects the GAC model based on image segmentation in the main function, and innovatively optimizes the stop function of its equation function, so as to improve the effect of community case image segmentation. …”
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Control Strategy for PHEB Based on Actual Driving Cycle with Driving Style Characteristic by Jianping Gao, Zhenhai Xu, Xiaojie Gao

“…Based on the 6 driving cycles, the key parameters of rule-based control strategy are optimized and established by a combinatorial optimization algorithm in Isight. …”
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Phase diagram from nonlinear interaction between superconducting order and density: toward data-based holographic superconductor by Sejin Kim, Kyung Kiu Kim, Yunseok Seo

“…We introduce positional embedding layers to improve the learning process in our algorithm, and the Adam optimization is used to predict the critical temperature data via holographic calculation with appropriate accuracy. …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Experimental results demonstrate that RIM-Net achieves an average accuracy of 92.36% on benchmark datasets while maintaining generalization capabilities above 85% in unseen environments. Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…This study investigates the application effectiveness of deep learning-based object detection technology in forest fire smoke recognition by using the YOLOv11x algorithm to develop an efficient fire detection model. …”
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Estimating Soil Cd Contamination in Wheat Farmland Using Hyperspectral Data and Interpretable Stacking Ensemble Learning by Liang Zhong, Meng Ding, Shengjie Yang, Xindan Xu, Jianlong Li, Zhengguo Sun

“…Ultimately, the SHAP method was used to shed light on the model’s decision-making process. The results show that (1) FOD can further highlight the spectral features, thereby strengthening the correlation between soil Cd content and wavelength; (2) the CARS algorithm extracted 3.4–6.8% of the feature wavelengths from the full spectrum, and most of them were the wavelengths with high correlation with soil Cd; (3) the optimal estimation precision was achieved using the FOD1.5-SNV spectral pre-processing combined with the Stacking model (<i>R</i>² = 0.77, RMSE = 0.05 mg/kg, RPD = 2.07), and the model effectively quantitatively estimated soil Cd contamination; and (4) SHAP further revealed the contribution of each base model and characteristic wavelengths in the Stacking modeling process. …”
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Research Status and Development Trends of Deep Reinforcement Learning in the Intelligent Transformation of Agricultural Machinery by Jiamuyang Zhao, Shuxiang Fan, Baohua Zhang, Aichen Wang, Liyuan Zhang, Qingzhen Zhu

“…This paper proposes research directions from three key dimensions-“algorithm capability enhancement, deployment architecture optimization, and generalization ability improvement”-offering theoretical references and practical pathways for the continuous evolution of intelligent agricultural equipment.…”
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Reliability Prediction for Computer Numerical Control Machine Servo Systems Based on an IPSO-Based RBF Neural Network by Zheng Jiang, GuangJian Wang, ZuGuang Huang, Ye He, RuiJuan Xue

“…A novel reliability prediction model based on radial basis function (RBF) neural network optimized by improved particle swarm optimization (IPSO) was proposed. …”
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Industrial-Grade 3D Detection for Laser Cleaning of Metallic Components Based on Neural Radiance Fields and Temporal-Spatial Learning by Dandan Qi

“…Improve the collaborative modeling ability between multi-temporal images through cross-scale attention fusion; 4. …”
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Research on the evaluation method of cooperative jamming effectiveness based on IPSO-ELM by A. Tianjian Yang, B. Xing Wang, C. Siyi Cheng, D. You Chen, E. Xi Zhang

“…This optimization aims to boost the model’s predictive precision. …”
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Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets by Mojtaba Fereydani, Mohammad Amin Latify

“…A column & constraint generation (C&CG) algorithm is used to solve the model. Numerical results demonstrate the model’s effectiveness in various case studies, showing that the GenCo can manage wind uncertainties, benefit from arbitrage opportunities in electricity and gas markets, and improve economic outcomes. …”
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Research on False Alarm Rate Reducing Strategies for Subway Train Fire Alarm System by ZHANG Qian, XU Shaohong, XUE Hongquan

“…The false alarm rate can be reduced by hardware optimization methods such as adding dust filter devices, adopting dual light source detectors, multi-parameter gas detectors and pyrolysis particle detectors; the rate can also be reduced by optimizing software algorithms (optimization modeling method, automatic adjustment of alarm thresholds, machine self-learning algorithm, etc.). …”
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基于modeFRONTIER的离合器碟形弹簧多目标优化设计 by 潘金坤

“…Based on the analysis of the working characters of disc springs in clutch,the mathematical model of multi-objective optimal design of disc springs is established with unified objective function method,which regards the minimization of the disc spring volume and its average variable quantity of working compress force within the scope of friction lining wear as optimal objectives.The optimization calculation is presented by using the software modeFRONTIER.The results indicate that the relevant performance of disc springs is significantly improved after optimal design,with the objective function values reduced by 36% and 6% respectively.The software modeFRONTIER,with its simplicity and efficient algorithm,solves optimization problems and improves design efficiency.…”
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