Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…A convolutional neural network (CNN) based on the VGG16 architecture is utilized for spatial feature extraction, followed by a bidirectional long short-term memory (BiLSTM) network to capture the temporal dependencies of the scalograms. The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
Get full text

Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

“…These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
Get full text

Optimizing performance and economic viability of combined energy systems: A novel energy hub framework by Dan Wang, Chenlin Ying

“…To solve this complex optimization problem, the spider monkey optimization (SMO) algorithm is modified and applied. …”
Get full text

Innovative real data-driven multi-objective optimization for sustainable energy in Siwa Oasis, Egypt using HYCHOPSO by Hosam Abdelhadi, Ahmed Mohamed Mahmoud, Ebtisam Mostafa Mohamed Saied, Mohamed Ahmed Ebrahim

Get full text

Improvement of the technique applied to preserve species and varieties of <i>Fragaria</i> L. in the field genebank at Krymsk Experiment Breeding Station of VIR by V. N. Podorozhniy, N. A. Piyanina

Get full text

Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model by Mahir Mohammed Sharif Adam, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Samah Al Zanin

“…In this paper, an enhanced assistive Technology for Blind People through Object Detection Using a Hiking optimization algorithm (EATBP-ODHOA) technique is proposed. …”
Get full text

Quantum Marine Predator Algorithm: A Quantum Leap in Photovoltaic Efficiency Under Dynamic Conditions by Okba Fergani, Yassine Himeur, Raihane Mechgoug, Shadi Atalla, Wathiq Mansoor, Nacira Tkouti

Get full text

Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Abstract The purpose of this study was to model and optimize the removal of methylene blue using a novel magnetic chitosan-carboxymethyl cellulose/multiwalled carbon nanotubes and to identify the most significant parameters influencing the adsorption efficiency. …”
Get full text

Opposition-based learning techniques in metaheuristics: classification, comparison, and convergence analysis by Rihab Lakbichi, Farouq Zitouni, Saad Harous, Aridj Ferhat, Abdelhadi Limane, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…In recent years, opposition-based learning (OBL) has emerged as a powerful enhancement strategy in metaheuristic algorithms (MAs), gaining significant attention for its potential to accelerate convergence and improve solution quality. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text