Firefly algorithm with multiple learning ability based on gender difference by Wenning Zhang, Chongyang Jiao, Qinglei Zhou

“…Abstract The Firefly Algorithm (FA), while effective for complex optimization, suffers from inherent limitations such as search oscillation and low convergence precision. …”
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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. …”
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Optimizing Hyperparameters in Meta-Learning for Enhanced Image Classification by Amala Mary Vincent, P. Jidesh, A. A. Bini

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Machine Learning Application for Improving Customer and Postal Logistics Operator Satisfaction in Urban Areas – A Review by Adisa MEDIĆ, Amel KOSOVAC, Ermin MUHAREMOVIĆ, Muhamed BEGOVIĆ

“…The significance of this research is highlighted through the identification of shortcomings in existing literature, offering guidelines for future research in developing new machine learning model for optimal operator selection. This model aims to achieve improvements in both customer and operator satisfaction simultaneously.…”
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2D DOA Estimation of Wideband and FH Signals Using Improved K-means Clustering and Implementation Considerations by Zahra Memarian, Mahdi Majidi

“…Simulation results demonstrate improved DOA estimation accuracy in multipath conditions, particularly at longer distances, with further enhancements achieved through the proposed clustering method.…”
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Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

“…By comparing the coupled neuron model optimized with a reinforcement learning algorithm, particle swarm algorithm, and quantum particle swarm algorithm, the experimental results show that the coupled neuron model optimized with a deep reinforcement learning algorithm has the optimal signal-to-noise ratio of the output signal and recognition rate of the bearing faults, which are −13.0407 dB and 100%, respectively. …”
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Numerical Design Structure Matrix–Genetic Algorithm-Based Optimization Method for Design Process of Complex Civil Aircraft Systems by Qiucen Fan, Yanlong Han, An Zhang, Wenhao Bi

“…The algorithm NSGA-II is improved and verified with the flight control system design as a case study. …”
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Modeling, optimization, and thermal management strategies of hydrogen fuel cell systems by Abubakar Unguwanrimi Yakubu, Liu Qingsheng, Meng Kai, Chen Jinwei, Omer Abbaker Ahmed Mohammed, Jiahao Zhao, Qi Jiang, Xuanhong Ye, Junyi Liu, Qinglong Yu, Muhammad Aurangzeb, Shusheng Xiong

“…Optimization algorithms such as PSO, WOA, MIGA, and NSGA-II have shown promising results, including up to 15 % reduction in hydrogen consumption and 20 to 30 % improvement in thermal uniformity. …”
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Enhanced ANN-Based MPPT for Photovoltaic Systems: Integrating Metaheuristic and Analytical Algorithms for Optimal Performance Under Partial Shading by Alpaslan Demirci, Idriss Dagal, Said Mirza Tercan, Hasan Gundogdu, Musa Terkes, Umit Cali

“…The results demonstrate that the improved ANN-based MPPT algorithm consistently outperforms existing MPPT techniques, including the Perturb and Observe (P&O) and Grey Wolf Optimization (GWO), Harris Hawks Optimization (HHO), and Particle Swarm Optimization (PSO) methods. …”
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Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S. by Bishwoyog Bhattarai, Zachary Leasor, André Fróes de Borja Reis

“…Leveraging machine learning (ML) techniques capable of handling large-scale datasets offers a promising alternative for uncovering hidden patterns and generating actionable insights to improve crop yield. We hypothesize that incorporating soil moisture and temperature data from land surface models into a ML framework will enhance accuracy of corn yield predictions. …”
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Implementation ofVision PSOFastSLAM Algorithm for Unmanned Aerial Vehicles in Mine Environment by LIU Shu-chi, YANG Wei

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Research on Local Obstacle Avoidance Path Planning Algorithm for Autonomous Mining Trucks by HUANG Shuai, WANG Jia, HUANG Jiade, HUANG Peng, LYU Liang

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Synergistic integration of refined pelican optimization algorithm and deep neural networks for autonomous vehicle control in edge computing architectures by Fude Duan, Bing Han, Xiongzhu Bu

“…The chief contributions of the present study have been threefold: (1) the improvement of a particular autonomous driving method optimized for mobile edge computing platforms; (2) the arrangement of an optimized MobileNet method employing the RPO algorithm that uses LiDAR sensor data for effective object recognition and path design; and (3) the construction of an indoor vehicle prototype by mean of a microcontroller and LiDAR sensors, after a comprehensive performance evaluation of inference models, and analyzing the trade-offs between input size and computational effectiveness. …”
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Enhancing Network Performance in Mitigating the Impact of Traffic Accidents with Full User Information by Seyyed Nader Shetab Boushehri, Hossain Poorzahedy, Reza Mahmoudi

“…Additionally, we propose a model for addressing the Accident Improvement Problem and put forth a heuristic algorithm to solve this model. …”
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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.…”
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Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

“…To classify the ripe and unripe pistachios with a small-sized and high test accuracy model, a two-layer CNN architecture’s hyperparameters were optimized with the proposed algorithm. …”
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Intelligent adjustment and energy consumption optimization of the fresh air system in hospital buildings based on Fuzzy Logic and Genetic Algorithms by Jing Peng, Maorui He, Mengting Fan

“…Meanwhile, it introduces the Genetic Algorithm (GA) and Fuzzy Logic Algorithm (FLA) to optimize the BPNN, thus enhancing the model’s global search ability and robustness. …”
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Prediction of chloride concentration in concrete under multi-salt environment: Optimization of integrated algorithm based on MSCPO and interpretability analysis by Daming Luo, Kanglei Du, Ditao Niu

“…The Improved Mixture Self-Adaptation Crested Porcupine Optimizer (MSCPO) optimized hyperparameters for XGBoost, LightGBM, and Catboost models separately. …”
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Combined Use of Spectral and Structural Features for Improved Early Detection of Pine Shoot Beetle Attacks in Yunnan Pines by Yujie Liu, Youqing Luo, Run Yu, Lili Ren, Qi Jiang, Shaoshun He, Xinqiang Chen, Guangzhao Yang

“…In conclusion, this study identified optimal spectral and structural variables for UAV monitoring and improved HRS model accuracy and thereby provided technical support for the IPM of PSB outbreaks.…”
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Optimal AC Power Flow with Energy Storage and Renewable Energy: An Efficient RL Algorithm Capable of Handling Equality Constraints by Mingde Liu, Jianquan Zhu, Mingbo Liu

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