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.…”
Get full text

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

Optimizing Cancer Detection: Swarm Algorithms Combined with Deep Learning in Colon and Lung Cancer using Biomedical Images by HariKrishna Pathipati, Lova Naga Babu Ramisetti, Desidi Narsimha Reddy, Swetha Pesaru, Mashetty Balakrishna, Thota Anitha

“…Eventually, the whale optimization algorithm (WOA) is used to optimally choose the hyperparameters of the CNN‐BiGRU model. …”
Get full text

Recent advancements in stereolithography (SLA) and their optimization of process parameters for sustainable manufacturing by Asmaul Husna, Salahuddin Ashrafi, ANM Amanullah Tomal, Noshin Tasnim Tuli, Adib Bin Rashid

“…Furthermore, the paper discusses the application of optimization methods like Genetic Algorithms and Artificial Neural Networks (ANN) to analyze, refine, and determine the optimal processing parameters for stereolithography. …”
Get full text

An optimized proportional resonant current controller based genetic algorithm for enhancing shunt active power filter performance by Behnam Amini, Hasan Rastegar, Mohammad Pichan

“…Therefore, by performing accurate and optimal adjustments for APF control, system performance and power quality level can be improved significantly. …”
Get full text

AI-Driven Identification of Grapevine Fungal Spores via Microscopic Imaging and Feature Optimization with Cuckoo Search Algorithm by Xin Shi, Seyed Mohamad Javidan, Yiannis Ampatzidis, Zhao Zhang

Get full text

Research on run-time overhead of RM and improvement by LUO Ding-ding, ZHAO Hai, SUN Pei-gang, ZHANG Xi-yuan, YIN Zhen-yu

Get full text

Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions by Leonardo Buscarini, Paola Romano, Elena Sofia Cocco, Carlo Damiani, Sanaz Pournajaf, Marco Franceschini, Francesco Infarinato

“…This process involved variables recoding, scaling, and the evaluation of different dataset balancing methods to optimize model performance. Following a thorough review and comparison of algorithms commonly employed in the clinical-rehabilitative field, the Random Over Sampling (ROS) technique, in combination with the Random Forest (RF) machine learning model, was selected. …”
Get full text

An improved synergistic dual-layer feature selection algorithm with two type classifier for efficient intrusion detection in IoT environment by G Logeswari, K Thangaramya, M Selvi, J. Deepika Roselind

Get full text

Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence by Manish Sharma Timilsina, Yuvraj Chaudhary, Prikshya Bhattarai, Bibek Uprety, Dilip Khatiwada

Get full text

IoT driven healthcare monitoring with evolutionary optimization and game theory by Shitharth Selvarajan, Hariprasath Manoharan, Taher Al-Shehari, Nasser A. Alsadhan, Subav Singh

“…The model is validated through four case studies, demonstrating an average improvement of 60% over existing methodologies. …”
Get full text

A Framework for Breast Cancer Classification with Deep Features and Modified Grey Wolf Optimization by Fathimathul Rajeena P.P, Sara Tehsin

“…A modified Grey Wolf Optimization algorithm with three significant adjustments improves feature selection and redundancy removal over the previous approach. …”
Get full text

Hybrid RSA-ROA Scheduling Algorithm for Minimization of Power Loss and Improving the Renewable with Sustainable Energy Harvesting in Power System by Cuddapah Anitha, Virendra Swaroop Sangtani, Ajay Kumar Bansal, Mahaveerakannan R., R. Rajesh Sharma, Saravanan M. S.

Get full text

Beyond boundaries: AI-optimized global landslide susceptibility mapping by Mahdi Panahi, Fatemeh Rezaie, Khabat Khosravi, Zahra Kalantari, Sayed M. Bateni, Jeong-A Lee

“…This study addresses these gaps by developing an optimized framework using support vector regression (SVR) enhanced with meta-heuristic algorithms (grey wolf optimizer [GWO] and bat algorithm) to refine model hyper-parameters. …”
Get full text

Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks by Manal Abdullah Alohali, Hamed Alqahtani, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K., Jaehyuk Cho

“…The methodology consists of three key phases: (1) Data preprocessing, where missing values are handled using the multiple imputations by chain equation (MICE) technique and feature scaling is applied using standard and min-max scalers; (2) Feature selection, where the FFXO algorithm reduces feature dimensionality to enhance classification efficiency; and (3) Lung tumor classification, utilizing Bi-GAN to improve predictive accuracy. …”
Get full text

Enhanced multi-level K-means clustering and cluster head selection using a modernized pufferfish optimization algorithm for lifetime maximization in wireless sensor networks by Anjana Koyalil, Sivacoumar Rajalingam

“…Additionally, the absence of clustering in certain models compromises the network capacity. To tackle these challenges, a new multi-level clustering technique with a heuristic optimization algorithm is proposed in this research work. …”
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

VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…It also requires fewer parameters and takes minimum training time. • The major contribution of this study is the design of an optimized, efficient and enhanced deep learning technique for multiclass rice crop disease detection embracing with batch normalization, dropout and genetic optimization algorithm to improve generalization power and restrict the overlearning capability for seen and unseen data. • Proposed VCNet, a shallow model with deep feature extraction, employs VGG16 layers for initial extraction fused with custom CNN architecture to correctly detect the challenging classes of diseases like sheath rot in multiclass classification. • The most significant observation is that VCNet accurately predicts the rice disease for each class of diseases under study whereas the existing powerful models largely misclassified for some classes of diseases in multiclass classification.…”
Get full text

An intelligent framework for sarcasm detection in Arabic tweets using deep learning with Al-Biruni earth radius optimization algorithm by Reema G. AL-anazi, Muhammad Swaileh A. Alzaidi, Majdy M. Eltahir, Wafa Sulaiman Almukadi, Samah Hazzaa Alajmani, Abdulbasit A. Darem, Mohammed Alshahrani, Nawaf Alhebaishi

Get full text

A Novel Modified Gorilla Troops Optimizer Algorithm for Interline Power Flow Controller-Based Damping Controller Design by Rajendra Kumar Khadanga, Deepa Das, Sidhartha Panda, Soumya Ranjan Mahapatro, Manoj Kumar Kar, Ahmed Al Mansur, Taha Selim Ustun, Akhtar Kalam

“…Based on the simulation results, the updated strategy that has been suggested is the most effective way to define the mentioned damping controller by considering the percentage improvement in the goal function value.…”
Get full text