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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A Q-Learning Crested Porcupine Optimizer for Adaptive UAV Path Planning by Jiandong Liu, Yuejun He, Bing Shen, Jing Wang, Penggang Wang, Guoqing Zhang, Xiang Zhuang, Ran Chen, Wei Luo

“…To address these issues, this paper proposes an algorithm named QCPO, which integrates CPO with Q-learning to improve UAV path optimization performance. …”
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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

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Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

“…Results from benchmark tests and case studies indicate that the improved MP–GWO algorithm outperforms the grey wolf optimizer (GWO), pelican optimizer (POA), Harris hawks optimizer (HHO), coyote optimizer (CPO), and particle swarm optimizer (PSO) in solving more complex optimization problems, providing better average results, greater stability, and effectively reducing flight time and path cost. …”
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Remaining useful life prediction of a small sample of aero-engine based on an improved gray Markov model by Dong-hai Li, Ji-liang Tu, Hui Liu, Nai-zhi Liao

“…To enhance adaptability, a genetic algorithm dynamically optimizes the time response parameters of the grey model, overcoming the limitation of a fixed structure in traditional methods. …”
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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm by F.Z. Zahraoui, H.E. Chakir, M. Et-taoussi, H Ouadi

“…The grid-connected SMG consists of photovoltaic (PV) cells, BSS, and residential loads. A Genetic Algorithm (GA)-based method is proposed to optimize power management in three scenarios: (i) active power only (AOM), (ii) active and reactive power without line losses (ARM), and (iii) active and reactive power considering line losses (ARLM). …”
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Optimization Strategy of Multi-group Inspection Path of Distribution Equipment with Equipment Information Included by Chaoqiang CHEN, Hanyang GONG, Di ZHANG, Zhidan ZHANG, Jian LE

“…A distribution equipment information model is established, and a multi group distribution equipment routing optimization model is proposed to minimize the total routing cost, which is solved by genetic algorithm. …”
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Anti-Collision Path Planning and Tracking of Autonomous Vehicle Based on Optimized Artificial Potential Field and Discrete LQR Algorithm by Chaoxia Zhang, Zhihao Chen, Xingjiao Li, Ting Zhao

“…Comparative analysis of visual trajectories pre-optimization and post-optimization highlights improvements. …”
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Indirect tuning of a complementary orientation filter using velocity data and a genetic algorithm by Dariusz Maton, John T. Economou, David Galvão Wall, Irfan Khan, Robert Cooper, David Ward, Simon Trythall

“…In this paper, the accuracy of inertial sensor orientation relative to the level frame is improved through optimal tuning of a complementary filter by a genetic algorithm. …”
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Path Planning of Underground Robots via Improved A* and Dynamic Window Approach by Jianlong Dai, Yinghao Chai, Peiyin Xiong

“…To overcome these challenges, we propose an improved path planning algorithm integrating an enhanced A* method with an improved Dynamic Window Approach (DWA). …”
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Hybrid optimized data aggregation for fog computing devices in internet of things by M. Jalasri, S. Manikandan, Arthur Davis Nicholas, S. Gobimohan, Naarisetti Srinivasa Rao

“…In this work, a new and novel hybrid optimization technique based on TABU Search (TS), Particle Swarm Optimization (PSO), and River Formation Dynamics (RFD) algorithms were proposed. …”
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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…Additionally， the Dijkstra algorithm is improved to plan charging paths more effectively by including real-time road condition data. …”
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Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints by Sheng Zou, Xuanjun Zong, Quan Chen, Wang Zhang, Hongwei Zhou

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Enhanced COVID-19 Optimization Algorithm for Solving Multi-Objective Optimal Power Flow Problems with Uncertain Renewable Energy Sources: A Case Study of the Iraqi High-Voltage Gri... by Basim ALBaaj, Orhan Kaplan

“…This paper introduces an enhanced version, the enhanced COVID-19 optimization algorithm (ENHCOVIDOA), designed to improve the performance of the original method. …”
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A Bi-Level Optimization Scheme for Energy Storage Configuration in High PV-Penetrated Distribution Networks Based on Improved Voltage Sensitivity Strategy by Bo Gao, Qing Du, Gonghao Zhan, Jian Han

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Multi-Robot Cooperative Simultaneous Localization and Mapping Algorithm Based on Sub-Graph Partitioning by Wan Xu, Yanliang Chen, Shijie Liu, Ao Nie, Rupeng Chen

“…First, a global matching and candidate loop selection strategy is incorporated into the front-end loop detection module, leveraging both LiDAR point clouds and visual features to achieve cross-robot loop detection, effectively mitigating computational redundancy and reducing false matches in collaborative multi-robot systems. Second, an improved distributed robust pose graph optimization algorithm is proposed in the back-end module. …”
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Research on Optimum Design of Waste Recycling Network for Agricultural Production by Huabin Wu, Jing Zhang, Yanshu Ji, Yuelong Su, Shumiao Shu

“…Second, based on the characteristics of APW, with the minimization of recycling transportation costs as the optimization objective, an ant colony algorithm was used to establish a corresponding vehicle scheduling route optimization model, yielding the optimal solution for recycling vehicle scheduling and transportation route optimization. …”
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Techno-economic optimization of hybrid renewable systems for sustainable energy solutions by Kanaga Bharathi N, Manoharan Abirami, Devi Vighneshwari, Manoharan Hariprasath

“…The scope includes defining parameter, sensitivity analysis, and optimization using iterative algorithms which are complex. …”
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Structural Optimization-Based Enhancement of the Dynamic Performance for Horizontal Axis Wind Turbine Blade by Ahmed Zarzoor, Alaa Jaber, Ahmed Shandookh

“…It employs a complex optimization framework that combines aerodynamics and structural analysis via MATLAB and a genetic algorithm. …”
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An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

“…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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