FinSafeNet: securing digital transactions using optimized deep learning and multi-kernel PCA(MKPCA) with Nyström approximation by Ahmad Raza Khan, Shaik Shakeel Ahamad, Shailendra Mishra, Mohd Abdul Rahim Khan, Sunil Kumar Sharma, Abdullah AlEnizi, Osama Alfarraj, Majed Alowaidi, Manoj Kumar

“…FinSafeNet draws attention to the attack and reproductive phases of Hierarchical Particle Swarm Optimization (HPSO) feature selection technique simulating it in a battle for extreme time performance called the Improved Snow-Lion optimization Algorithm (I-SLOA). …”
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An Integrated Learning Approach for Municipal Solid Waste Classification by Hieu M. Sondao, Tuan M. Le, Hung V. Pham, Minh T. Vu, Son Vu Truong Dao

“…During the feature selection phase, three metaheuristic algorithms—Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA), and Harris Hawk Optimization (HHO)—are applied to filter out irrelevant features and retain significant ones. …”
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Construction and scheduling optimization of renewable energy consumption forecasting system for twisted tire porcelain manufacturing industry based on deep learning by Fangrong Liao, Runlin Ran, Jiayi Zhang

“…After the algorithm is trained on GPU many times, the obtained optimal model is tested many times in the above data set, with an accuracy rate of 90.2% and a speed of 66 frames per second. …”
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Improved firefly algorithm–extended Kalman filter–least-square support-vector machine voltage sag monitoring and classification method based on edge computing by Zhu Liu, Xuesong Qiu, Yonggui Wang, Shuai Zhang, Zhi Li

“…Extract characteristic quantities such as average value, duration of sag, minimum sag dispersion characteristics, number of sag phases, and flow direction of disturbance energy. As a model training data set, the least-square support-vector machine method optimized based on the improved firefly algorithm is used to create a multi-level classification model of voltage sag source to realize the classification of voltage sag sources. …”
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Demand side management with electric vehicles and optimal renewable resources integration under system uncertainties by Mohamed Mostafa Eissa, Rania Abdel Wahed Swief, Tarek Saad Abdel Salam

“…The study utilizes the Zebra optimization algorithm (ZOA), in comparison with the Whale optimization algorithm (WOA), Grey wolf optimization algorithm (GWO), and Genetic algorithm (GA). …”
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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

“…We also present the Spider Wasp Optimization (SWO) algorithm, which aims to improve performance by feature selection. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Abstract Artificial intelligence has revolutionized various industries, including chemical process optimization. Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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An optimized public opinion communication system in social media networks based on K-means cluster analysis by Mingchao Qi, JunQiang Zhao, Yan Feng

“…This study proposes a public opinion monitoring model that combines the K-means clustering algorithm with Particle Swarm Optimization (PSO) to enhance the accuracy and effectiveness of public opinion monitoring on social media. …”
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Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking by Athanasios Sidiropoulos, Dimitrios Bechtsis, Dimitrios Vlachos

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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…This work presents a stochastic two-stage mixed-integer nonlinear programming (MINLP) optimization model for the long-term planning of a distribution system (DS) to improve renewable energy integration over a ten-year period. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
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Multi-energy System Planning and Configuration Study for Low-Carbon Parks Based on Comprehensive Optimization Objectives by Yang WANG, Fei LU, Ji LI, Zhukui TAN, Zongyu SUN, Wei XU, Zihong SONG, Zhenpeng LIU

“…Secondly, by taking a multi-energy system with triple supply of cooling, heating and power system coupled with ground source heat pump, energy storage, and gas boiler in a typical low-carbon park as an example, a comparative analysis was made on the configuration results and optimization speed with different optimization algorithms, and a study was conducted on the impacts of different optimization objectives such as optimal comprehensive optimization objective and lowest whole life-cycle cost and energy consumption on the capacity optimization configuration results and typical daily operation situation. …”
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Integrating AI Deep Reinforcement Learning With Evolutionary Algorithms for Advanced Threat Detection in Smart City Energy Management by Fenghua Liu, Xiaoming Li

“…The integration of Deep Reinforcement Learning (DRL) with Evolutionary Algorithms (EAs) represents a significant advancement in optimizing smart city energy operations, addressing the inherent uncertainties and dynamic conditions of urban environments. …”
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A genetic algorithm-based solution for multi-type maximal covering location problem (MMCLP): application to defense and deterrence by J.D. Lessan, Geoff Pond

“…Design/methodology/approach – In our case study, we use open source geographic and demographic data from Canadian sources as inputs to our optimization problem. Due to the complexity of the MIP formulation, we propose a hybrid metaheuristic solution approach, for which a genetic algorithm (GA) is proposed and integrated with local and large neighborhood search operators. …”
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An Interpretable Data-Driven Dynamic Operating Envelope Calculation Method Based on an Improved Deep Learning Model by Yun Li, Tunan Chen, Jianzhao Liu, Zhaohua Hu, Yuchen Qi, Ye Guo

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A Theoretical Bound Which Improves the Performance of Compilation-Based Multi-Agent Path Finding by Rodrigo Lopez, Roberto Asin-Acha, Jorge A. Baier

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Optimization Design of Lazy-Wave Dynamic Cable Configuration Based on Machine Learning by Xudong Zhao, Qingfen Ma, Jingru Li, Zhongye Wu, Hui Lu, Yang Xiong

“…Three optimization algorithms—Particle Swarm Optimization (PSO), Ivy Optimization (IVY), and Tornado Optimization (TOC)—were evaluated for their effectiveness in optimizing the arrangement of buoyancy and weight blocks. …”
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Improved A* Algorithm Based on Artificial Potential Field Method for Global Path Planning of Unmanned Surface Vessels in Complex Environments by Shuxuan Liu, Zhijia Qian, Sunwei Jiang, Quanming Miao

“…In the improved A* algorithm, the search direction was first optimized, simplifying the traditional eight direction search to a “target point attracts four directions” search, significantly reducing the ineffective expansion nodes of the traditional algorithm, reducing algorithm running time, and improving search efficiency; Secondly, on the basis of improving the cost function, the idea of artificial potential field algorithm is integrated, and the repulsive function is introduced. …”
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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Ruiqin Duan, Xiaosheng Peng, Cong Li, Zimin Yang, Yan Jiang, Xiufeng Li, Shuangquan Liu

“…Wind power prediction (WPP) is necessary to the safe operation and economic dispatch of power systems. In order to improve the prediction accuracy of WPP, in this paper we propose a three-step model named SDAE-SVR-BA to be applied in short-term WPP based on stacked-denoising-autoencoder (SDAE) feature processing, bat algorithm (BA) optimization and support vector regression (SVR). …”
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Dynamic weighted ensemble model for predictive optimization in green sand casting: Advancing industry 4.0 manufacturing by Rajesh V․ Rajkolhe, Dr. Sanjay S․ Bhagwat, Dr. Priyanka V․ Deshmukh

“…The gains were statistically significant (p < 0.05) based on paired t-test analysis, confirming that DWE offers superior prediction consistency.The proposed DWE model supports real-time optimization in green sand casting, helping reduce defects and improve quality outcomes. …”
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