Mobile Robot Path Planning Based on Enhanced Dynamic Window Approach and Improved A∗ Algorithm by Hongxia Yang, Xingqiang Teng

“…In the improved A∗ algorithm, in order to improve the algorithm efficiency, so that a single planning path can pass through multiple target points, the search point selection strategy and evaluation function are optimized. …”
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A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…Olives are a crucial woody oil crop, the harvesting of which predominantly relies on manual labor, which is characterized by high costs, low efficiency, and challenges in ensuring optimal harvesting timing. …”
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Study on Piping Layout Optimization for Chiller-Plant Rooms Using an Improved A* Algorithm and Building Information Modeling: A Case Study of a Shopping Mall in Qingdao by Xiaoliang Ma, Hongshe Cui, Yan Zhang, Xinyao Wang

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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

“…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. …”
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Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks by Nadia Shamshad, Lei Wang, Kiran Saleem, Danish Sarwr, Salil Bharany, Ahmad Almogren, Jaeyoung Choi, Ateeq Ur Rehman, Ayman Altameem

“…This paper proposes a KNN-based cost-efficient machine-learning algorithm aimed at optimizing underwater context acquisition with sensor nodes. …”
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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…Such an integration acted as regular convolutional layers that subsequently substituted for the original layers to cut computational costs. Furthermore, we adopted the SIoU loss function, a modified version of CIoU, applied to the YOLOv8s model, demonstrating a substantial improvement in accuracy. …”
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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…Feature selection is often used by some researchers to overcome these problems, because these methods have an important function in the process of reducing data dimensions and eliminating uncorrelated attributes that can cause noisy. Naive Bayes algorithm is used to support the process of determining the most optimal class. …”
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Improved Nonprobabilistic Global Optimal Solution Method and Its Application in Bridge Reliability Assessment by Xiaoya Bian, Xuyong Chen, Hongyin Yang, Chen You

“…Utilizing the improved one-dimensional optimization algorithm conveniently solved the nonprobabilistic reliability index, however, only searching the part of probable failure points. …”
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Magnetic targets positioning method based on multi-strategy improved Grey Wolf optimizer by Binjie Lu, Zongji Li, Xiaobing Zhang

“…Therefore, a Multi-Strategy Improved Grey Wolf Optimizer (MSIGWO) algorithm has been proposed to enhance the accuracy of magnetic target state estimation. …”
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Sugarcane Feed Volume Detection in Stacked Scenarios Based on Improved YOLO-ASM by Xiao Lai, Guanglong Fu

“…At the stereo matching level, we enhance the SGBM (Semi-Global Block Matching) algorithm through improved cost calculation and cost aggregation, resulting in Opti-SGBM (Optimized SGBM). …”
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Optimization of fuzzy bottleneck cost transportation models in the decision framework of congruence modulo technique by Kapil Kumar, Nandini, Tarun Kumar, Kailash Dhanuk, Anirudh Kumar Bhargava, M.K. Sharma

“…This article investigates the Congruence Modulo algorithm and time freezing method as innovative solutions for addressing fuzzy bottleneck cost transportation problems. …”
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Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies by Lixin Mu, Wenhui Liu, Haocheng Wang, Yu Zhang

“…To enhance UAV adaptability in such environments, improve rapid and efficient path planning capabilities, and reduce operational costs, this paper proposes a 3D UAV path planning algorithm based on an improved Dwarf Mongoose Optimization (DMO) algorithm enhanced with multiple strategies. …”
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A design method of composite pixel-like antenna based on improved bald eagle search algorithm by WANG Yongqiang, LIU Bingqi, ZHU Bolin

“…This method not only retains the good convergence of the original algorithm, but also partially improves the global search ability. …”
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Problems of optimizing the energy consumption of households in the tasks of improving the energy efficiency of the housing sector by G. G. Grebenuk, S. M. Nikishov, A. A. Krygin, L. A. Sereda

“…The most important results of the work performed are the following:• the methodology for forecasting the graph of the maximum totalpower consumption has been developed.• methods for optimizing energy consumption for each of the selected subsets of household appliances have been developed.• the optimization algorithms obtained have been simulated, which showed their operability, efficiency and the possibility of their practical application without any adaptation.Thus, the article proposes the solution of the problem of optimization of energy consumption in the housing sector, oriented to practical application.…”
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Cost-Effective Optimization of Sizing and Charging Profiles for PHEV Parking Lots in Smart Microgrids Using Harmony Search Algorithm by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Emad M. Ahmed, Zaki A. Zaki, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

“…However, EV participation significantly reduces ohmic losses and improves the grid load profile. The proposed HS algorithm outperforms the DE algorithm by achieving lower microgrid costs and better convergence efficiency. …”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Among the available methods, partial transmit sequence (PTS) is an efficient PAPR reduction method but can be computationally expensive while deter-mining optimal phase factors (OPFs). Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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YOLOv8-DBW: An Improved YOLOv8-Based Algorithm for Maize Leaf Diseases and Pests Detection by Xiang Gan, Shukun Cao, Jin Wang, Yu Wang, Xu Hou

“…The experimental results showed that the precision, recall, and mAP0.5 of the improved algorithm were improved by 1.4, 1.1, and 1.5%, respectively, compared with YOLOv8n, and the model parameters and computational costs were reduced by 6.6 and 7.3%, respectively. …”
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GIRH-Unet: Improved Residual Tobacco Segmentation Algorithm Based on GhostNetV3-Unet by Jianhua Ye, Yunda Zhang, Pan Li, Ze Guo

“…Our approach utilizes an improved GhostNetV3 to bolster feature extraction capabilities. …”
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Improved Ant Colony Optimization for the Operational Aircraft Maintenance Routing Problem with Cruise Speed Control by Qing Zhang, Felix T. S. Chan, Xiaowen Fu

“…Accordingly, the goal of this study is twofold: (i) to design a preprocessing step to reduce the network size and (ii) to develop an improved ant colony optimization (IACO) algorithm with a new state transition mechanism to provide the guidance for cruise times optimization and a new pheromone updating mechanism to enhance the search efficiency and precision. …”
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An efficient hybrid filter-wrapper method based on improved Harris Hawks optimization for feature selection by Jamshid Pirgazi, Mohammad Mehdi Pourhashem Kallehbasti, Ali Ghanbari Sorkhi, Ali Kermani

“…Conclusion: The two-stage hybrid method effectively selects the optimal subset of features, improving the performance of classification algorithms on high-dimensional datasets. …”
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