The Utilization of a Naïve Bayes Model for Predicting the Energy Consumption of Buildings by Behnam Sadaghat, Ali Javadzade Khiavi, Babak Naeim, Erfan Khajavi, Hadi Sadaghat, Amir Reza Taghavi Khanghah

“…These algorithms are employed to improve HVAC system control, equipment sizing, energy management, and cost reduction. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…The results indicate that all three driving forces significantly enhance the overall level of urban-rural integration, with the most substantial improvements observed in economic and social integration. …”
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Integrating GIS, 3D-Isovist, and an NSGA-II multi-objective optimization algorithm for automation of design process in urban parks and public open spaces by Karim Zandniapour, Akram Soroush, Ehsan Khezerlu Agdam, Haniyeh Sanaieian

“…The results showed that the NSGA-II was able to solve the complex design problem with 185 trees and 66 observers. The algorithm produced a Pareto-frontier consisting of four optimal solutions that, compared to the existing state of the park, showed more than 18% and 12 % improvement according to Tree View and Building View, respectively. …”
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Local corner smoothing based on deep learning for CNC machine tools by Bai Jiang, Rong Sun, Ze-long Li, Liang Xu, Huang Liao, Xiao-yan Teng, Bing Li

“…Considering the influence of population size and computational resources on intelligent optimization algorithms, a deep learning algorithm (the Double-ResNet Local Smoothing (DRLS) algorithm) is proposed to further improve optimization efficiency. …”
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Internet of things driven object detection framework for consumer product monitoring using deep transfer learning and hippopotamus optimization by Amnah Alshahrani, Mukhtar Ghaleb, Hany Mahgoub, Achraf Ben Miled, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Hasan Beyari, Sultan Alanazi

“…Additionally, the hippopotamus optimization algorithm (HOA)-based hyperparameter selection model is implemented to improve the classification result of the CAE technique. …”
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SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study by Abrar Yaqoob, Navneet Kumar Verma, Mushtaq Ahmad Mir, Ghanshyam G. Tejani, Nashwa Hassan Babiker Eisa, Hind Mamoun Hussien Osman, Mohd Asif Shah

“…Abstract In this study, we propose a novel approach for breast cancer classification that integrates the Seagull Optimization Algorithm (SGA) for feature selection with the Random Forest (RF) classifier for effective data classification. …”
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Efficient Technique for Joint Parameter Estimation of Mixed Far Field Targets and Near Field Jammers in Phased Array Radar by Fawad Zaman, Sadiq Akbar, Zohaib Akhtar, Gridsada Phanomchoeng

“…The GSR enhances the convergence rate and improves the exploration tendency to obtain the better solution in the search space, while the LEO helps the algorithm avoid getting stuck in the local optima. …”
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Multi-Factor Optimization and Failure-Tolerant Design of Cable-Driven Parallel Manipulators in Deep-Sea Robotics by Asim Ghaffar, Muhammad Zia Ur Rahman, Victor Leiva, Cecilia Castro, Carlos Martin-Barreiro

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Theoretical investigation of photonic spin Hall effect based on layered metastructure with graphene regulation by WOA for encoding and encryption by Na Pei, Ye Zheng, Yue-Qi Tang, Xing-Zhou Tang, Hai-Feng Zhang

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Multi-Stage and Multi-Objective Optimization of Solar Air-Source Heat Pump Systems for High-Rise Residential Buildings in Hot-Summer and Cold-Winter Regions by Zhen Wang, Jiaxuan Wang, Chenxi Lv

“…When optimizing the renewable energy system configuration of residential buildings for solar-air source heat pump systems, the optimization algorithm and the setting of parameter ranges will have an impact on the optimization results. …”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

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The human-on-the-loop evaluation of multiobjective optimization algorithms for solving a real-world problem that integrates the food-energy-water nexus security and climate change... by Isaac Okola, Daniel Orwa Ochieng, Evans Kirimi Miriti, Gilbert Ouma Ong'isa

“…Such research areas include incorporating machine learning to predict, using performance data, the most suitable algorithm to solve a specific problem, and advancing interactive learning and user adjustments of the optimization process.…”
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Robust Path Tracking Control with Lateral Dynamics Optimization: A Focus on Sideslip Reduction and Yaw Rate Stability Using Linear Quadratic Regulator and Genetic Algorithms by Karrar Y. A. Al-bayati, Ali Mahmood, Róbert Szabolcsi

“…To address this issue, this study proposes the optimization of the linear quadratic regulator (LQR) control system by using the genetic algorithm (GA) to support the vehicle in following the predefined path accurately, minimizing the sideslip, and stabilizing the vehicle’s yaw rate. …”
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Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm by Xiang Wu, Zhen Yang, Dongdong Wu

“…Moreover, adaptive particle swarm optimization (APSO) was used to optimize the penalty factor and kernel parameters of the support vector machine to improve the global search ability and avoid the occurrence of the local optimal solutions. …”
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Multi-objective optimization of current-assisted splitting spinning of small module tooth-shaped part based on the combination of BP neural network and NSGA-II algorithm by Zhou Haoyang, Xia Qinxiang, Xiao Gangfeng, Chen Can

“…The results show that the material at the tooth tip along the radial direction is in the state of tensile stress along radial and compressive stresses along tangential and axial directions, which promotes the radial flowing of the material and is beneficial the tooth filling of SMTSPs; the tooth saturation increases obviously under pulse current comparing without pulse current; the BPNN combined with the NSGA-II algorithm can reliably optimize the process parameters of the CASS, improving the forming quality of SMTSPs; experiments verified the feasibility of the process and the accuracy of the predictive model based on the optimization results.…”
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Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

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Prediction of CO2 emission for the central European countries through five metaheuristic optimization techniques helping multilayer perceptron by Hossein Moayedi, Azfarizal Mukhtar, Serhan Alshammari, Mohamed Boujelbene, Isam Elbadawi, Quynh T Thi, Mojtaba Mirzaei

“…To develop a reliable predictive network considering the problem complexity, multilayer perceptron (MLP) is combined with several nature-inspired optimization algorithms, namely, black hole algorithm (BHA), future search algorithm (FSA), backtracking search algorithm (BSA), biogeography-based optimization (BBO), and shuffled complex evolution (SCE). …”
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Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network by Amit Kumar Rai, Nirupama Mandal, Krishna Kant Singh, Ivan Izonin

“…The seed selection is done using the spectral indices to further improve the performance of the network. The manta ray foraging optimization algorithm is inspired by the intelligent behaviour of manta rays. …”
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A Two-echelon Model of Location-routing Problem for Optimizing Relief Operations in Natural Disasters by Hossein Jamali, Mehdi Kabiri Naeini, Zeynab Elahi

“…Conclusion The proposed model is an effective method to improve relief operations and strengthen crisis management during natural disasters.…”
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A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and... by Priya Mathur, Hammad Shaikh, Farhan Sheth, Dheeraj Kumar, Amit Kumar Gupta

“…In particular, autoencoder-based augmentation combined with hyperparameter optimization consistently improved predictive accuracy across all models. …”
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