Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…Meta-heuristic algorithms offer an alternative to traditional gradient-based optimizers for improving DNNs performance. …”
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Delay margin analysis of FOTID controller for RES based EV system using MMGPE optimization by Adhit Roy, Susanta Dutta, Soumen Biswas, Anagha Bhattacharya, Sajjan Kumar, Soham Dutta, Provas Kumar Roy

“…For a steady, continuous power supply, renewable energy has become one of the most promising substitutes for traditional energy sources in recent decades. …”
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A Dynamic Interval Auto-Scaling Optimization Method Based on Informer Time Series Prediction by Yu Ding, Chenhao Li, Zhengong Cai, Xinghao Wang, Bowei Yang

“…In the experiments conducted on the official World Cup forum load and Alibaba cluster CPU load, the Informer time series prediction algorithm demonstrated better long-sequence time series prediction capabilities compared to algorithms such as LSTM and RNN. …”
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Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…The wrapping method was identified as the most effective feature selection algorithm. Based on field conditions, 8 optimal features were selected for prediction. …”
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Artificial Intelligence and Nature-Inspired Techniques on Optimal Biodiesel Production: A Review—Recent Trends by Christos Kyriklidis, Aikaterini Koutouvou, Konstantinos Moustakas, Vayos Karayannis, Constantinos Tsanaktsidis

“…The optimal fuels are produced in laboratories and tested in common engines too. …”
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On the need of individually optimizing temporal interference stimulation of human brains due to inter-individual variability by Tapasi Brahma, Alexander Guillen, Jeffrey Moreno, Abhishek Datta, Yu Huang

“…Material and method: Here we aim to study the inter-individual variability of optimized TI by applying the same optimization algorithms on N = 25 heads using their individualized head models. …”
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Enhancing Power Efficiency in 4IR Solar Plants through AI-Powered Energy Optimization by S. Boobalan, TR. Kalai Lakshmi, Shubhangi N. Ghate, Mohammed Hameeduddin Haqqani, Sushma Jaiswal

“…The AI-powered system relies on intelligent algorithms to identify the most efficient energy sources for the industry’s needs and adjust them accordingly while learning from every task it is given. …”
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A Survey on Video Compression Optimization Techniques for Accuracy Enhancement in Video Analytics Applications (VAPs) by Kholidiyah Masykuroh, Hendrawan, Eueung Mulyana, Farhan Krishna

“…However, the efficiency of these applications depends on optimizing video compression parameters to maintain high detection accuracy while minimizing bandwidth usage and computational costs. …”
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Optimization Techniques for Physician Scheduling Problem: A Systematic Review of Recent Advancements and Future Directions by Norizal Abdullah, Masri Ayob, Meng Chun Lam, Nasser R. Sabar, Graham Kendall, Mohamad Khairulamirin Md Razali

“…Future research directions are outlined, emphasizing the need for more scalable algorithms, real-time scheduling capabilities, improved user interfaces, and comprehensive validation studies. …”
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Optimizing resource allocation in remote healthcare via blockchain-enabled decentralized networks and spectral clustering by A. Kanimozhi, K. Vidya

“…The proposed system utilizes the InterPlanetary File System (IPFS) to handle resource requests transparently and securely, while spectral and agglomerative clustering algorithms are employed to optimize delivery routes. …”
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Machine Learning for Chinese Corporate Fraud Prediction: Segmented Models Based on Optimal Training Windows by Chang Chuan Goh, Yue Yang, Anthony Bellotti, Xiuping Hua

“…We then implement the sliding time window approach to handle population drift, and the optimal training window found demonstrates the existence of population drift in fraud detection and the need to address it for improved model performance. …”
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An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

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An emotional neural network based approach for wind power prediction by Guoling ZHANG

“…To prevent ENN from stucking in locally optimal solution in the process of training, genetic algorithm was proposed to train ENN. …”
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Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…MaOSSO is shown to consistently outperform competing methods with up to 15–20% faster convergence and 25% less computation time. While applying the algorithm on the MaO-OPF problem, the active/reactive power loss minimization was optimized along with the voltage stability, emissions, operational cost, and Pareto front diversity sustaining. …”
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Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting by Farideh Sobhanifard

“…On the other hand, Particle Swarm Optimization is a computational approach, an intelligent optimization, and the most popular algorithm that has been widely used for performing such types of optimization problems, which has faster convergence. …”
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Enhancing shear strength predictions of UHPC beams through hybrid machine learning approaches by Sanjog Chhetri Sapkota, Ajad Shrestha, Moinul Haq, Satish Paudel, Waiching Tang, Hesam Kamyab, Daniele Rocchio

“…This study proposes hybrid ML models that integrate three nature inspired metaheuristic algorithms—Giant Armadillo Optimization (GOA), Spotted Hyena Optimization (SHO) and Leopard seal optimization (LSA)- Extreme Gradient Boosting (XGB) to predict the shear strength of UHPC beams. …”
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Advancing In Vivo Molecular Bioimaging With Optimal Frequency Offset Selection and Deep Learning Reconstruction for CEST MRI by Adarsha Bhattarai, Chathumi Samaraweera, Mariano Uberti, Aditya N. Bade, Yutong Liu, Dongming Peng

“…Firstly, we use an optimization algorithm to identify a set of optimal sparse frequency offsets for data collection. …”
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Multiperiod Location–Allocation Optimization of Construction Logistics Centers for Large-Scale Projects in Complex Environmental Regions by Hao Shen, Jin Zhang, Wenjie Sun, Wenguang Yang, Guoqi Li

“…Finally, a large-scale railroad construction project in complex environmental regions is used as an example to prove the effectiveness of the model and algorithm. Compared with the single-period model, the multiperiod model designed in this paper provides a total cost reduction of 8.11% for the CLC location–allocation scheme. …”
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Optimal Configuration of Additional Heat Source for CHP System considering Demand Response Based on Comprehensive Benefits by Yuting Zhao

“…Furthermore, an improved memetic algorithm (IMA) combined with a hierarchical sequence method is designed to solve the optimization model characterized by multiple objectives, hierarchical levels, and nonlinearity. …”
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Development of a Smart Waste Management System for Route Optimization and Adaptive Demand Management in Dubai by H. Hassan, T. Ali, A. Tamimi

“…This paper presents an overview of the development of a Smart Waste Management System (SWMS) that integrates Geographic Information System (GIS) technology with waste route optimization algorithms and adaptive demand management strategies. …”
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