Landslide Forecasting Model Based on PCA and Improved CS-RBF by WANG Lianxia, LI Limin, FANG Zihao, REN Ruibin, FU Zhentao, CUI Chengtao

“…The dimensionality-reduced data is then input into the RBF neural network for landslide probability forecasting. Secondly, an improved Cuckoo Search algorithm is used for parameter optimization to improve the accuracy of landslide probability forecasting. …”
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An Improved KF-RBF Based Estimation Algorithm for Coverage Control with Unknown Density Function by Lei Zuo, Maode Yan, Yaoren Guo, Wenrui Ma

“…Compared with the other estimation algorithms, a novel sampling regulation mechanism is designed to improve the estimation performance and reduce the computational load. …”
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A mobile app to improve adherence to colorectal cancer screening and post polypectomy surveillance guidelines by María A. Casas, Francisco Schlottmann, Leandro Steinberg, Xavier Bessa, Anna Serradesanferm, Angels Pozo, Sonia Torres, Antoni Castells, Francesc Balaguer, Jaume Grau, Lisandro Pereyra, María Pellisé

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An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem by Jianxia Zhang, Jianxin Zhang, Feng Zhang, Minglu Chi, Linbin Wan

“…In addition, two different kinds of practical examples were also adopted for algorithm evaluation. From the simulation results, it can be seen clearly that the costs of electric-power generation gained were the lowest compared with the results of particle swarm optimization algorithm, improved chaos particle swarm optimization algorithm, and symbiotic organisms search algorithm, well demonstrating the effectiveness of the improved symbiosis particle swarm optimization algorithm in solving the economic load dispatch problem.…”
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Increasing integration of wind energy through the joint operation of electric vehicles and the grid using the intelligent spider monkey algorithm by Han Xiaoming, Qian Jingjing

“…A significant innovation involves demonstrating that prohibitive constraints on simultaneous charging and discharging can, under specific conditions, be relaxed without compromising system stability, thereby simplifying the optimization process. The optimization problem is formulated as a single objective problem and solved using an improved spider monkey optimization algorithm. …”
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An Improved Spider Wasp Optimizer for Green Vehicle Route Planning in Flower Collection by Mengxin Lu, Shujuan Wang

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ClipQ: Clipping Optimization for the Post-Training Quantization of Convolutional Neural Network by Yiming Chen, Hui Zhang, Chen Zhang, Yi Liu

“…In response to the issue that post-training quantization leads to performance degradation in mobile deployment, as well as the problem that the balanced consideration of quantization deviation by Clipping optimization techniques limits the improvement of quantization accuracy, this article proposes a novel clipping optimization method named ClipQ, which pays different attention to the parameters, aiming to preferentially reduce the quantization deviation of important parameters. …”
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Long short‐term memory‐based forecasting of uncertain parameters in an islanded hybrid microgrid and its energy management using improved grey wolf optimization algorithm by Raji Krishna, Hemamalini S

“…Results demonstrate that the improved grey wolf optimization (IGWO) algorithm is more effective at reducing costs and provides faster optimal solutions.…”
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Puma algorithm for environmental emissions and generation costs minimization dispatch in power systems by Badr Al Faiya, Ghareeb Moustafa, Hashim Alnami, Ahmed R. Ginidi, Abdullah M. Shaheen

“…The POO algorithm consistently outperforms other algorithms in minimizing both generation and emission costs across all loading levels, with improvement percentages ranging from approximately 1.221 % to 1.6 % compared to OOA, 0.59 % to 0.86 % compared to AO, 2.47 % to 3.42 % compared to SMA, 0.89 % to 1.67 % compared to Coati and 0.03 % to 0.13 % compared to ARO. …”
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Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment by Xun Lu, Junlei Liu, Xinmiao Liu, Jun Liu, Lingxue Lin

“…The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. …”
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Synchronous End-to-End Vehicle Pedestrian Detection Algorithm Based on Improved YOLOv8 in Complex Scenarios by Shi Lei, He Yi, Jeffrey S. Sarmiento

“…To address these challenges, this paper proposes an improved vehicle and pedestrian detection algorithm based on YOLOv8, with the aim of enhancing detection in complex traffic scenes. …”
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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

“…This study proposes a novel approach for continuous knee joint angle prediction based on surface electromyography (sEMG), integrating an Improved Zebra Optimization Algorithm (IZOA) with an attention-enhanced Gated Recurrent Unit (GRU) network. …”
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Productivity Improvement of Garments Industry by Implementing Line Balancing Algorithms—A Case Study by Mst. Anjuman Ara, Nafisa Anjum, Dilir Ahbab, Mushfica Takia Sidiika, Risat Rimi Chowdhury

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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization by Muhammad Suhail Shaikh, Chang Wang, Senlin Xie, Gengzhong Zheng, Xiaoqing Dong, Shuwei Qiu, Mohd Ashraf Ahmad, Saurav Raj

“…This study presents an Improved Chaotic Grey Wolf Optimization (ICGWO) algorithm to enhance WSN coverage and connectivity while addressing challenges like high deployment costs, limited coverage, and insufficient connectivity. …”
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Exponential Improvements in the Simulation of Lattice Gauge Theories Using Near-Optimal Techniques by Mason L. Rhodes, Michael Kreshchuk, Shivesh Pathak

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Internet of Things Based Application Placement Technique in Fog Environment by N Malathy, M Ruba, S Vinothini

“…A pre-scheduling method is developed to efficiently allocate tasks by analyzing workflows to reduce computation delays and energy usage. Leveraging an Improved Memetic Algorithm (IMA), this strategy enables effective scheduling of parallel IoT workflows across fog and cloud servers, ensuring balanced resource utilization and enhanced scalability. …”
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Improving MPCitH with Preprocessing: Mask Is All You Need by Guowei Liu, Guoxiao Liu, Kaijie Jiang, Qingyuan Yu, Keting Jia, Puwen Wei, Meiqin Wang

“…The optimal signature implementation costs about 78% of the previous implementation time. …”
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The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…The primary objective of this method is to improve the operational efficiency of the power grid, reduce energy costs, and facilitate economical and efficient energy distribution in the power market. …”
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Multi-Objective Improved Differential Evolution Algorithm-Based Smart Home Energy Management System Considering Energy Storage System, Photovoltaic, and Electric Vehicle by Mina GhasemiGarpachi, Moslem Dehghani, Mokhtar Aly, Jose Rodriguez

“…A multi-objective improved differential evolution algorithm is used to solve the HEMSs. …”
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DPF-Bi-RRT^*: An Improved Path Planning Algorithm for Complex 3D Environments With Adaptive Sampling and Dual Potential Field Strategy by Lin Ge, Swee King Phang, Nohaidda Sariff

“…Additionally, a biased random sampling strategy improves computational efficiency by directing sampling resources toward sections with higher promise of optimal paths, dramatically reducing computational cost. …”
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