Improving forest above-ground biomass estimation using genetic-based feature selection from Sentinel-1 and Sentinel-2 data (case study of the Noor forest area in Iran) by Armin Moghimi, Ava Tavakoli Darestani, Nikrouz Mostofi, Mahdiyeh Fathi, Meisam Amani

“…Subsequently, GA was employed to select the most optimal features among them within both Random Forest (RF) and Multiple Linear Regression (MLR) models, leading to enhanced accuracy in the forest AGB estimation process. …”
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Landslide Forecasting Model Based on PCA and Improved CS-RBF by WANG Lianxia, LI Limin, FANG Zihao, REN Ruibin, FU Zhentao, CUI Chengtao

“…Various models including back propagation (BP), RBF, genetic algorithm-RBF (GA-RBF), CS-RBF, and others are compared with the improved CS-RBF model through experimental analysis. …”
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Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization by Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu, Peng Li

“…To address this challenge, we propose a novel prediction model that integrates an adaptive-weight particle swarm optimization (AWPSO) algorithm with a back propagation neural network (BPNN). …”
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Daily runoff forecasting using novel optimized machine learning methods by Peiman Parisouj, Changhyun Jun, Sayed M. Bateni, Essam Heggy, Shahab S. Band

“…This study addresses these challenges by introducing a novel bio-inspired metaheuristic algorithm, Artificial Rabbits Optimization (ARO), integrated with various machine learning (ML) models for runoff forecasting in the Carson and Chehalis River basins. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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Research on APF-Dijkstra Path Planning Fusion Algorithm Based on Steering Model and Volume Constraints by Xizheng Wang, Gang Li, Zijian Bian

“…Therefore, an APF-Dijkstra path planning fusion algorithm based on steering model and volume constraints is proposed to improve it. …”
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Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

“…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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Enhancing agricultural sustainability: Optimizing crop planting structures and spatial layouts within the water-land-energy-economy-environment-food nexus by Haowei Wu, Zhihui Li, Xiangzheng Deng, Zhe Zhao

“…In this framework, the NSGA-II algorithm was used to construct the multi-objective optimization model of crop planting structures with consideration of water and energy consumption, greenhouse gas (GHG) emissions, economic benefits, as well as food, land, and water security constraints, while the model for planting spatial layout optimization was established with consideration of crop suitability using the MaxEnt model and the improved Hungarian algorithm. …”
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Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike by Hojat Karami, Alireza Rezaei, Amin Atarodi

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Application of a hybrid algorithm of LSTM and Transformer based on random search optimization for improving rainfall-runoff simulation by Wenzhong Li, Chengshuai Liu, Caihong Hu, Chaojie Niu, Runxi Li, Ming Li, Yingying Xu, Lu Tian

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Courier Assignment and Routing Problem Algorithm in Online Food Delivery System with Multi-Customer Delivery Patterns by Prita Meilanitasari, Maulin Masyito Putri, Ilda Auly Sita Agustin, Muhammad Faisal Ibrahim, Dwi Sekar Arumjani

“…After processing and analyzing the numerical data, the study identified the most effective scenario that led to improved delivery times and benefits for couriers, enabling them to manage more orders and achieve faster delivery compared to existing algorithms. …”
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Identification Method for Resistance Coefficients in Heating Networks Based on an Improved Differential Evolution Algorithm by Enze Zhou, Yaning Liu, Minjia Du, Junli Yu, Wenxiao Xu

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An Improved Migratory Birds Optimization Algorithm for Closed- Loop Supply Chain Network Planning in a Fuzzy Environment. by Yangjun Ren, Qiong Chen, Yui-Yip Lau, Maxim A Dulebenets, Mengchi Li, Botang Li, Mark Ching-Pong Poo, Pengfei Zhang

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PID Control of Multisources Complex Excitations Active Vibration Isolation System: An Improved Particle Swarm Optimization Algorithm by Song Chunsheng, Jiang Youliang, Zhang Jinguang

“…Furthermore, this paper also sets up the acceleration feedback-based PID control model for multisources complex excitations active vibration isolation system, proposes an improved particle swarm optimization (PSO) algorithm of dynamic inertia weight factors used to optimize parameters of the built PID control model, and conducts simulation analysis. …”
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Energy Management of Electric–Hydrogen Coupled Integrated Energy System Based on Improved Proximal Policy Optimization Algorithm by Jingbo Zhao, Zhengping Gao, Zhe Chen

“…However, the inherent uncertainties of renewable energy sources present significant challenges to optimal energy management in the EHCS. To address these challenges, this paper proposes an energy management method for the EHCS based on an improved proximal policy optimization (IPPO) algorithm. …”
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Improved Monthly Runoff Prediction of OSELM Based on Secondary Decomposition Technique and Optimization of Ten "Bird" Swarm Algorithms by DENG Zhiyu, CUI Dongwen

“…To improve the accuracy of monthly runoff time series prediction and enhance the performance of online sequential extreme learning machine (OSELM) prediction, ten "bird" swarm algorithms were compared and validated for optimization, including satin bowerbird optimizer (SBO)/Harris hawks optimization (HHO)/seagull optimization algorithm (SOA)/African vultures optimization algorithm (AVOA)/coot optimization algorithm (COOT)/pelican optimization algorithm (POA)/eagle perching optimization (EPO)/osprey optimization algorithm (OOA). …”
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Knowledge reasoning and strategy optimization for ship operation and maintenance based on digital twin and improved KD tree algorithm by Liyao ZHANG, Ziqian GUO, Ruifang LI, Xun YE, Tao MA

“…Based on the database, a method for ship O&M knowledge reasoning and strategy generation using an improved KD tree algorithm is proposed. Neighboring cases are weighted using Gaussian distance weighting, and the whale optimization algorithm (WOA) is used to optimize the characteristic attributes of ship equipment to achieve accurate knowledge reasoning. …”
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Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. …”
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An Operation Optimization Strategy of the Combined Power Generation System with Wind Power & Pumped Storage Based on Improved Whale Algorithm by LI Kecheng, YANG Ning

“…In order to solve the model, based on the basic whale optimization algorithm, a multi-objective whale optimization algorithm is developed by adding external population and leader selection mechanism, and the control parameter in the algorithm is improved to obtain an improved multi-objective whale optimization algorithm. …”
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Generic optimal power flow solution associated with technical improvements and emission reduction by multi-objective ARO algorithm by Amlak Abaza, Ragab A. El-Sehiemy, Zakeria Elbarabry, Asmaa F. Barakat

“…This comparison validates the scalability and efficiency of the ARO algorithm. The impact of varied population size and maximum iteration number is tested for two test systems, the most benchmarking test systems. …”
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