A lightweight and optimized deep learning model for detecting banana bunches and stalks in autonomous harvesting vehicles by Duc Tai Nguyen, Phuoc Bao Long Do, Doan Dang Khoa Nguyen, Wei-Chih Lin

“…Notably, the proposed model outperforms the previous detection models, offering high accuracy while optimizing computational efficiency. …”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

“…In this manuscript, an Underwater Object Detection and Classification Utilizing the Ensemble Deep Learning Approach and Hybrid Optimization Algorithms (UODC-EDLHOA) technique is developed. …”
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Hybrid optimization for efficient 6G IoT traffic management and multi-routing strategy by J. Logeshwaran, Shobhit K. Patel, Om Prakash Kumar, Fahah Ahmed Al-Zahrani

“…Data was successfully routed using a hybrid Quantum Genetic Algorithm and Ant Colony Optimization (QGA-ACO) approach. …”
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Evaluation method for gas pre-extraction status in coal seam boreholes based on semi-supervised learning by YAN Li, WEN Hu, WANG Zhenping, JIN Yongfei

“…Building on this, a semi-supervised learning model based on the Gaussian mixture model (GMM) and K-Means algorithm (SSGMM/SSK-Means) was developed. …”
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A Smooth Jump Point Search Algorithm for Mobile Robots Path Planning Based on a Two-Dimensional Grid Model by Zhen Yang, Junli Li, Liwei Yang, Hejiang Chen

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Joint Service Caching and Computing Offloading Strategies for Electrical Equipment Intelligent IoT Platform by Yi SUN, Shaonan CHANG, Kai CHEN, Qiang CUI, Weijie SHEN

“…The simulation results show that the proposed strategy can effectively improve the task processing efficiency, reduce the computing cost of suppliers, and improve the service revenue of the service providers.…”
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Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM by Xueting Bai, Chunwen Pu, Wenchong Zhen, Yushuang Huang, Qian Zhang, Zihan Li, Yixin Zhang, Rongxuan Xu, Zhihan Yao, Wei Wu, Mei Sun, Xiaofeng Li

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Hybrid adaptive ant lion optimization with traditional controllers for driving and controlling switched reluctance motors to enhance performance by Mostafa Jabari, Davut Izci, Serdar Ekinci, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…To address these issues, this work introduces a novel hybrid adaptive ant lion optimization (HAALO) algorithm, combined with PI and FOPID controllers, to improve SRM performance. …”
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SIMULATION AND OPTIMIZATION AS A TOOL FOR THE DEVELOPMENT OF HIGH EFFECTIVE TECHNOLOGICAL SCHEMES OF DISTILLATION by A. V. Timoshenko, E. A. Anokhina

“…This method has unfortunately been very energy intensive and requires a lot of heat. Mathematical modeling of the technological schemes of distillation is an effective method to improve existing and to create new industrial technologies. …”
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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

“…Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. …”
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Exploring Advanced Methodologies for Hybrid Energy System Sizing through Artificial Intelligence Techniques: a comprehensive review by Walid Bensalmi, Ahmed Belhani, Abdellatif Bouzid-Daho

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Surface Reconstruction Planning with High-Quality Satellite Stereo Pairs Searching by Jinwen Li, Guangli Ren, Youmei Pan, Jing Sun, Peng Wang, Fanjiang Xu, Zhaohui Liu

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Multi-Objective Optimization of Daylighting–Thermal Performance in Cold-Region University Library Atriums: A Parametric Design Approach by Yunong Gao, Shuting Zhao, Yong Huang, Hui Pan

“…In this paper, we take the library project in the cold region as a practical case, use the measured data to support the simulation experiment, combine the parametric platform and multi-objective coupling optimization algorithm to carry out digital modeling, and explore the dynamic relationship between the atrium light, heat environment, and the value of energy consumption under the influence of a variety of parameters. …”
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Optimizing Multi-Quay Combined Berth and Quay Crane Allocation Using Computational Intelligence by Sheraz Aslam, Michalis P. Michaelides, Herodotos Herodotou

“…First, the study develops a mathematical model representing a real port environment and then adapts the cuckoo search algorithm (CSA) for the first time in this setup. …”
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Optimizing Security of Radio Frequency Identification Systems in Assistive Devices: A Novel Unidirectional Systolic Design for Dickson-Based Field Multiplier by Atef Ibrahim, Fayez Gebali

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Coordinated multi-objective optimization scheduling for electric vehicle swapping station cluster and grid by Xiang Liao, Ziyu Zheng, Beibei Qian, Haiwei Wang, Dianling Zhan, Junyi Shi, Chaoshun Li, Wei Huang

“…Meanwhile, an electricity mutual assistance strategy between EVBESS is proposed to improve overall energy efficiency. Subsequently, an improved many-objective optimization algorithm based on multiple update strategies (G-MOMUS) is used to solve the model. …”
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Smart deep learning model for enhanced IoT intrusion detection by Faisal S. Alsubaei

“…The optimized SNN model also performed well on the NSL-KDD dataset with an accuracy of 99.0% and an AUC of 1.00. …”
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Maximum Torque per Ampere Control of PMSMs Using Real-Time Numerical Optimization by Yong Xu, Min-Yi Lin, Wen-Jie Wan, Yunchong Wang, Jian-Xin Shen

“…A flux-linkage based nonlinear PMSM model was developed to improve the torque control under dynamic conditions. …”
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