Optimizing additive manufacturing workflows using model-based systems engineering by Mohamed Amine Daoud, Khadija Bekkay Haouari, Meriem Hayani Mechkouri, Amine Ennawaoui, Hicham El hadraoui, Ilias Naser, Mustapha Ouardouz, Kamal Reklaoui

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Improvement of the Voltage Profile and Loss Reduction in Distribution Network Using Moth Flame Algorithm: Wolaita Sodo, Ethiopia by S. Balakumar, Akililu Getahun, Samuel Kefale, K. Ramash Kumar

“…There are several techniques that emerged to solve problems in the power system to provide quality and uninterrupted supply to customers. The algorithms used in this paper to determine the appropriate location and size of the Static Var Compensator (SVC) in the Distribution Network (DN) are Moth Flame Optimization (MFO) and Particle Swarm Optimization (PSO). …”
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Adaptive Improved Q-Learning Path Planning Algorithm Based on Obstacle Learning Matrix and Artificial Potential Field by Lieping Zhang, Hongyuan Chen, Xiaoxu Shi, Jianchu Zou, Yilin Wang

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Application of Convolutional Neural Network (CNN) Algorithm with ResNet-101 Architecture for Monkey Pox Detection in Human by Al Fathir Rizal Januar, Jamaludin Indra, Dwi Sulistya Kusumaningrum, Sutan Faisal

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A Low-Frequency Oscillation Identification Method for Power System Based on Adaptive Generalized S-Transform with Bat Algorithm by Miao Yu, Jingjing Wei, Shuoshuo Tian, Jianqun Sun, Yixiao Wu, Shouzhi Zhang, Jingxuan Hu

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Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems by Saud S. Alotaibi, Turki Ali Alghamdi

“…This study presents a League Championship Algorithm Feature Selection with Optimal Deep Learning based Cyberattack Detection (CLAFS-ODLCD) technique for securing the digital ecosystem. …”
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Optimal nodes selection in wireless sensor and actor networks based on prioritized mutual exclusion approach by VIRENDER RANGA, Mayank Dave, Anil K. Verma

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Intelligent Data Reduction for IoT: A Context-Driven Framework by Laercio Pioli, Douglas D. J. De Macedo, Daniel G. Costa, Mario A. R. Dantas

“…This approach differs from existing work by using contextual relevance to guide the dynamic selection of Data Reduction (DR) algorithms, predicting results rather than computing them, which significantly reduces computational overhead. …”
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Fast-converging decentralized alternating direction method of multipliers for consensus optimization by Jeannie He, Ming Xiao, Mikael Skoglund

“…To tackle these challenges, we introduce two novel decentralized ADMM algorithms to enable decentralized learning without incurring redundant computations, excessive message transmissions, or extended convergence time. …”
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Stable matching-enhanced MOEA/D for solving multi-objective optimal power flow problems by Ebrahim Akbari, Amin Khodabakhshian, Abolfazl Rahimnejad, Stephen Andrew Gadsden

“…The proposed method ensures a balanced and effective trade-off between solution accuracy and diversity in multi-objective optimization. Comparative evaluations against well-established algorithms demonstrate the superior performance of the proposed approach in approximating the Pareto front, improving computational efficiency, and maintaining solution diversity. …”
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Towards Optimizing the Downlink Transmit Power in UAV-Integrated IRS Wireless Systems by Ali Reda, Tamer Mekkawy, Ashraf Mahran

“…Simulation results demonstrate that the proposed SCA algorithm provides an efficient transmit power minimization approach with low computational complexity for large IRS since it achieves close-to-optimal performance, and significantly outperforms conventional systems without IRS. …”
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The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…Abstract This study addresses key challenges in optimizing agricultural industry structures and facilitating intelligent transformation through the application of deep learning algorithms and advanced optimization techniques. …”
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Link Scheduling and End-to-End Throughput Optimization in Wireless Multi-Hop Networks by Fei Ge, Liansheng Tan, Wei Zhang, Ming Liu, Xun Gao, Juan Luo

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Stochastic Multiple Chaotic Local Search-Incorporated Gradient-Based Optimizer by Hang Yu, Yu Zhang, Pengxing Cai, Junyan Yi, Sheng Li, Shi Wang

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Seismic Performance-Based Total Cost Optimization for Steel Moment-Resisting Frames by Akram Abdulazeez-Ali-ALbalky, Saeed Gholizadeh, Saeed Tariverdilo

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Dynamic Optimization of Recurrent Networks for Wind Speed Prediction on Edge Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Muhammad Asim, Samia Allaoua Chelloug, Mohammed A. ELAffendi

“…Server-dependent machine learning models, commonly deployed in wind farms, prove infeasible for domestic systems due to high costs and energy demands. While edge computing offers a viable alternative, current WSP methods prioritize hyperparameter optimization without constraining model size (MS), resulting in memory-intensive architectures incompatible with resource-limited devices. …”
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Output Feedback Adaptive Optimal Control of Multiple Unmanned Marine Vehicles with Unknown External Disturbance by Liang-En Yuan, Yang Xiao, Tieshan Li, Dalin Zhou

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Application of quasi-oppositional driving training-based optimization for a feasible optimal power flow solution of renewable power systems with a unified power flow controller by Tushnik Sarkar, Chandan Paul, Susanta Dutta, Provas Kumar Roy, Ghanshyam G. Tejani, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

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Insurance claims estimation and fraud detection with optimized deep learning techniques by P. Anand Kumar, S. Sountharrajan

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INEH-VNS Algorithm Solved Automatic Production System Scheduling Problem under Just-in-Time Environment by Li Qingxiang, Zhao Xiaofei, He Yude, Yin Shaojun

“…Compared with the G-VNS algorithm, the average improvement rate of the approximate optimal solution is 45.9%, and the average stability rate of the INEH-VNS algorithm enhances 75.04%. …”
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