Optimization of integrated energy system considering P2G oxygen-enriched improvement and hybrid solar energy utilization by Xiaohui YANG, Zhao WAN, Riying XIAO, Zeyu YANG, Zecheng HU, Chilyu WU

“…The simulation results show that the CO2 emissions are reduced by 75.83% compared to the oxygen-enriched improvement before, and the total solar energy output is increased by 9.79% compared to the scenario without combined solar energy, indicating that the proposed model can effectively reduce carbon emissions and operating costs.…”
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Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

“…For the combined RGB and MS data, spectral indices were the important input features for the SGPR and VHGPR models. The optimized mND705 was selected as the most critical spectral indices for PNC prediction. …”
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Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…This study presents Cybersecurity using a Crested Porcupine Optimizer Algorithm with Hybrid Deep Learning Models (CCPOA-HDLM). …”
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A solution to the Single-School school bus routing problem considering accessibility and economy by Zizhan Jiang, Jiying Wang, Siyuan Huang, Hua Daniel Xu

“…A well-designed SBRP strategy can reduce the operating costs of the school bus system, improve accessibility, and ensure timely arrival for teachers and students. …”
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Multi-Timescale Battery-Charging Optimization for Electric Heavy-Duty Truck Battery-Swapping Stations, Considering Source–Load–Storage Uncertainty by Peijun Shi, Guojian Ni, Rifeng Jin, Haibo Wang, Jinsong Wang, Zhongwei Sun, Guizhi Qiu

“…The key contributions include the following: (1) the development of a battery-charging model for electric heavy-duty truck battery-swapping stations that accounts for the uncertainty in the power output of energy sources, loads, and storage; (2) the proposal of a day-ahead battery-charging optimization algorithm based on intra-day-optimization feedback information-gap decision theory (IGDT), which allows for dynamic adjustment of risk preferences; (3) the proposal of an intra-day battery-charging optimization algorithm based on an improved grasshopper optimization algorithm, which enhances algorithm convergence speed and stability, avoiding local optima. …”
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Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State by Emmanuel Gbenga Dada, Aishatu Ibrahim Birma, Abdulkarim Abbas Gora

“…The proposed WAEL model ingeniously combines five feature spaces through the grey wolf optimisation (GWO) algorithm to uncover the optimal weight combination. …”
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Enhanced OCR Recognition for Madurese Text Documents: A Genetic Algorithm Approach with Tesseract 5.5 by Muhammad Nazir Arifin, Muhammad Umar Mansyur, Ali Rahman, Nindian Puspa Dewi, Fauzan Prasetyo Eka Putra

“…Character Recognition (OCR) for the Madurese language using Genetic Algorithms (GA). The study addresses the challenges in processing Madurese text documents by implementing a nine-step image preprocessing workflow optimized through GA. …”
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Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 by Riya Karmakar, Sandip Chatterjee, Debabrata Datta, Dipankar Chakraborty

“…ARIMA is one such model that has been widely used for this purpose, but in most cases, the model was not optimized suitably. …”
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Advanced Vehicle Routing for Electric Fleets Using DPCGA: Addressing Charging and Traffic Constraints by Yuehan Zheng, Hao Chang, Peng Yu, Taofeng Ye, Ying Wang

“…With the rapid proliferation of electric vehicles (EVs), urban logistics faces increasing challenges in optimizing vehicle routing. This paper presents a new modeling framework for the Electric Vehicle Routing Problem (EVRP), where multiple electric trucks serve a set of customers within their capacity limits. …”
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A two stage differential evolution algorithm for parameter estimation of proton exchange membrane fuel cell by Mohammad Aljaidi, Sunilkumar P. Agrawal, Pradeep Jangir, Sundaram B. Pandya, Anil Parmar, Arpita, Ali Fayez Alkoradees, Bhargavi Indrajit Trivedi, Mohammad Khishe

“…Most traditional parameter estimation methodologies depend on optimization algorithms which are limited in their efficiency, convergence speed, and robustness. …”
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LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects by Xiaolin WU, Ling LUAN, Lianwu PAN, Hailong LI

“…Compared with the BP neural network and GD-CNN, the proposed model with higher prediction accuracy and stability combines the advantages of Levenberg-Marquart algorithm and convolutional neural network model to improve the calculation effect of power transmission and transformation project cost.…”
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Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…The use of optimization methods, graph algorithms, forecasting, and machine learning to improve the efficiency of digital systems is investigated. …”
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Prediction of cardiovascular disease based on multiple feature selection and improved PSO-XGBoost model by Kerang Cao, Chang Liu, Siqi Yang, Yuxin Zhang, Lili Li, Hoekyung Jung, Shuo Zhang

“…In order to predict it more accurately, this paper proposes a cardiovascular disease prediction model that combines multiple feature selection, improved particle swarm optimization algorithm, and extreme gradient boosting tree. …”
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Improvements of particle filter optimization algorithm for robust optimization under different types of uncertainties by Éva Kenyeres, Alex Kummer, János Abonyi

“…This paper presents a widely usable sampling-based methodology by improving the Particle Filter Optimization (PFO) algorithm. …”
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Mathematical modelling and optimization of cutting conditions in turning operation on MDN 350 steel with carbide inserts by Syed Adil, A. Krishnaiah, D. Srinivas Rao

“…Genetic Algorithm, which is an advanced optimization technique known for its intricate search for optimal solutions, is used for optimizing surface roughness with optimal combination of the geometrical parameters. …”
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Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm by Dawei Wang, Bo Gao, Lei Zhang

“…This paper introduces an innovative algorithm, the improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. …”
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Framework for truck–RPAS hybrid models in last-mile delivery by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte

“…High-quality Pareto-optimal solutions are produced by the non-dominated sorting genetic algorithm II, which methodically manages trade-offs between the conflicting goals. …”
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The Hub Location and Flow Assignment Problem in the Intermodal Express Network of High-Speed Railways and Highways by Xiaoting Shang, Zhenghang Wang, Xin Cheng, Xiaoyun Tian

“…Owing to the NP-hard computational complexity, an improved genetic algorithm with local search is designed by combining the genetic operators and two optimization strategies to solve the problem effectively. …”
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FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…This paper proposes a federated learning approach based on the dung beetle optimizer, named FedDBO. In this method, the model parameters uploaded from clients to the server are transformed into model scores. …”
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Online Vulnerability Assessment in Cascading Failure Analysis Using an Intelligence Monitoring Model by Saber Armaghani, Zahra Moravej

“…Thus, in this paper, Demand Response modeling will be based on determining the cost of electric energy consumption in the emergency of the network in such a way as to cause a shift of consumption to improve the performance of the network. …”
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