Optimization of computer network security system based on improved neural network algorithm and low energy data search by Miao Zhigang, Cao Ying, Wang Tao

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Optimization of CO2 water-alternating-gas injection parameters based on an improved hunger game search algorithm by WU Gongyi, SUN Yuxin, SUN Xiaofei, JI Hongming, ZHANG Yanyu

“…This new approach formed an improved hunger game search algorithm based on chaotic mapping functions, allowing for collaborative intelligent optimization between the algorithm and reservoir simulation software. …”
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A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system by Geetanjali Dei, Deepak Kumar Gupta, Binod Kumar Sahu, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…The controller’s parameters are optimized using an advanced Coatis Optimization Algorithm (COA). …”
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Multi-UAV path planning considering multiple energy consumptions via an improved bee foraging learning particle swarm optimization algorithm by Yuanhang Qi, Haoran Jiang, Gewen Huang, Liang Yang, Fujie Wang, Yunjian Xu

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Cross-Modal Behavioral Intelligence in Regard to a Ship Bridge: A Rough Set-Driven Framework with Enhanced Spatiotemporal Perception and Object Semantics by Chen Chen, Yuenan Wei, Feng Ma, Zhongcheng Shu

“…To address these challenges, this paper proposes a cross-modal behavioral intelligence framework designed specifically for a ship’s bridge, integrating multi-target tracking, behavior recognition, and feature object association. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…This systematic review investigates the integration of artificial intelligence (AI) in cost estimation within project management, focusing on its impact on accuracy and efficiency compared to traditional methods. …”
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Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social... by A. A. Poguda, H. Tape

“…The aim of this research is to develop an intelligent system for processing semistructured data from comments on social media videos using structuring algorithms targeting different industries. …”
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Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

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Migration and mutation (MeTa) hybrid trained ANN for dynamic spectrum access in wireless body area network by Geoffrey Eappen, Shankar T, Rajesh A

“…The novel MeTa hybrid optimization algorithm achieves a balance between global and local search abilities by optimizing the weights of the ANN. …”
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The dual-edged potential of AI autonomously defining loss functions by Abbas Ghori

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Two-Layer Intelligent Learning Control Using Output Recurrent Fuzzy Neural Long Short-Term Memory Broad Learning System With RMSprop by Ali Rospawan, Ching-Chih Tsai, Chi-Chih Hung

“…This paper proposes a novel two-layer intelligent learning control framework to address these issues, integrating an output recurrent fuzzy neural long short-term memory broad learning system (ORFNLSTM-BLS) with a root mean squared propagation (RMSprop) optimization algorithm. …”
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Multi-objective recommendation system utilizing a multi-population knowledge migration framework by Liang Chu, Ye Tian

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An Application of Artificial Intelligence for the Joint Estimation of Amplitude and Two-Dimensional Direction of Arrival of Far Field Sources Using 2-L-Shape Array by Fawad Zaman, Ijaz Mansoor Qureshi, Junaid Ali Khan, Zafar Ullah Khan

“…In these proposed artificial intelligence techniques, the metaheuristics based on genetic algorithm and simulated annealing are used as global optimizers assisted with rapid local version of pattern search for optimization of the adaptive parameters. …”
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Fine-Tuning Quadcopter Control Parameters via Deep Actor-Critic Learning Framework: An Exploration of Nonlinear Stability Analysis and Intelligent Gain Tuning by Hassan Moin, Umer Hameed Shah, Muhammad Jawad Khan, Hasan Sajid

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Provide a Solution Based on Teacher and Student Learning Algorithm to Reduce Regression Test Cases by Mahmood Deypir, Amirhossein Mohammadpour

“…In other words, the purposes of test selection methods is to reduce the number of test cases after changing the code and focus on identifying the modified parts of the program. Intelligent methods such as regression improve the accuracy of tests in software projects, and the use of optimization algorithms to find the optimal amount of test cases can be useful in terms of time and speed, and according to research by examining and optimizing this algorithm in the system. …”
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Artificial intelligence based classification and prediction of medical imaging using a novel framework of inverted and self-attention deep neural network architecture by Junaid Aftab, Muhammad Attique Khan, Sobia Arshad, Shams ur Rehman, Dina Abdulaziz AlHammadi, Yunyoung Nam

“…The extracted features are fused using a modified serial fusion with a strong correlation approach. An optimization algorithm- slap swarm controlled standard Error mean (SScSEM) has been employed, and the best features that passed to the shallow wide neural network (SWNN) classifier for the final classification have been selected. …”
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Improved fish swarm algorithm based on chaos and its application in abnormal detection of industrial control network by Yaping WU, Hongzhao DONG, Yingying LIN, Jing LIU

“…Artificial fish swarm algorithm as a new type of bionic swarm intelligence optimization algorithm has been successfully used in a variety of optimization problems and practical engineering field,but when faced with the complex optimization problems,especially the multiple extreme value of peak and multimodal function optimization problems,due to the objective function has many local minima,inevitably there are defects such as premature and slow convergence speed.The random and ergodic theory was introduced into the basic artificial fish swarm algorithm,and an improved algorithm was constructed to make artificial fish swarm search avoid possible local extremum.The effectiveness of the algorithm was validated in the simulation application in industrial control network anomaly detection.Compared with the basic artificial fish school algorithm,the chaos improved artificial fish swarm algorithm can effectively avoid the long-term search of the algorithm near the local extreme value.The algorithm has better performance in terms of global convergence and the search efficiency is more prominent.…”
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An Improved Gaining Sharing Knowledge-Based Algorithm for Solving Resource Allocation Problems by Ayman Kamal, Heba Said Roshdy, Naglaa Ragaa Said Hassan, Ali Wagdy Mohamed

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Optimization and Trends in EV Charging Infrastructure: A PCA-Based Systematic Review by Javier Alexander Guerrero-Silva, Jorge Ivan Romero-Gelvez, Andrés Julián Aristizábal, Sebastian Zapata

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Hybrid Population-Based Hill Climbing Algorithm for Generating Highly Nonlinear S-boxes by Oleksandr Kuznetsov, Nikolay Poluyanenko, Kateryna Kuznetsova, Emanuele Frontoni, Marco Arnesano

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