Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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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

“…Furthermore, the system can be customized according to your industry’s changing needs and requirements, providing the ability to reduce costs in energy usage while improving the efficiency and productivity of machines.…”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”
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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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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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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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Optimal Adjustment Schemes on the Long Through-Type Bus Lines considering the Urban Rail Transit Network by Si-Jia Zhang, Shun-Ping Jia, Yun Bai, Bao-Hua Mao, Cun-Rui Ma, Tong Zhang

“…It is of great importance to optimize the schemes of long through-type bus lines to adapt to the urban rail transit network. …”
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UTILIZING QUANTUM-ENHANCED DYNAMIC CLUSTERING FOR OPTIMIZED PATH SELECTION IN WBANS FEATURING OPTICAL BIOSENSORS TECHNOLOGY by Poonam Sharma, Kamaljit Singh Saini, Prabhjot Kaur

“…The simulated results are compared with the existing algorithms, and it is found that the performance of the proposed algorithms is improved by 65.6% and 53.3% in terms of TEC, 7.2% and 7.3% in terms of PDR, 33.9% and 45.8% in terms of E2D from ACSO and Dragonfly Optimization respectively. …”
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An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions by Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa

“…GMSMFO enhances population diversity and avoids local optima through Gaussian mutation (GM), while the shrink mechanism (SM) improves exploration–exploitation balance. Validated on the congress on evolutionary computation (CEC2020) benchmark suite (dimensions 30 and 50), GMSMFO demonstrated superior performance compared to other optimization algorithms. …”
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Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Existing AutoCIL methods focus solely on single-objective optimization. However, real-world applications often involve multiple, conflicting objectives—such as predictive performance and computational cost—that must be jointly optimized. …”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…The data show that the optimized root mean square error (RMSE) value under level 5 sea conditions is 0.01265 compared to 0.01673 before optimization, and the optimized RMSE value under level 6 sea conditions is 0.01140 compared to 0.01479 before optimization, which demonstrates that the error between the predicted value and the actual value of the model decreases. …”
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Optimal location and size of electric vehicle charging and discharging stations in distribution networks with integrated distributed generations by Minh Thien Vo, Thi Lan Anh Tran, Quang Ai Nguyen, Trung Khanh Tran, Ngoc Dieu Vo

“…In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. …”
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Optimal location and size of electric vehicle charging and discharging stations in distribution networks with integrated distributed generations by Minh Thien Vo, Thi Lan Anh Tran, Quang Ai Nguyen, Trung Khanh Tran, Ngoc Dieu Vo

“…In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. …”
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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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Superior terahertz radiation detection through novel micro circular log-periodic antenna engineered with an advanced evolutionary neural network algorithm by Rui Zhou, Jiaqi Wang, Zhemiao Xie, Yonghai Sun, Guanxuan Lu, John T. W. Yeow

“…Abstract In this work, we introduce a novel Micro Circular Log-Periodic Antenna (MCLPA) optimized with an advanced Evolutionary Neural Network (ENN) algorithm, specifically designed to enhance terahertz (THz) radiation detection. …”
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Application of the Bidirectional Encoder Representations from Transformers Model for Predicting the Abbreviated Injury Scale in Patients with Trauma: Algorithm Development and Vali... by Jun Tang, Yang Li, Keyu Luo, Jiangyuan Lai, Xiang Yin, Dongdong Wu

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A Concise Review of Home Health Care Routing and Scheduling Problem by Soumen Atta, Vítor Basto-Fernandes, Michael Emmerich

“…The study examines various optimization approaches, including exact algorithms, heuristics, and metaheuristic techniques. …”
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Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance by Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen-Quan Tao

“…The GSA module uses the Sobol method to evaluate the impact of design variables on performance. The optimization module employs the Newton-Raphson-based optimizer (NRBO) and the multi-strategy improved grey wolf optimization algorithm (MIGWO). …”
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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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Route Optimization of Hazardous Material Railway Transportation Based on Conditional Value-at-Risk Considering Risk Equity by Liping Liu, Shilei Sun, Shuxia Li

“…This research offers practical decision support for transport companies and regulators, helping optimize routes while ensuring cost efficiency and regulatory compliance. …”
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