Recurrent Neural Network Optimized by Grasshopper for Accurate Audio Data-Based Diagnosis of Parkinson's Disease by Saif Wali Ali Alsudani, Ghassan Khudair Saud

“… Proposed here is a speech-based diagnostic framework for detecting Parkinson's disease that utilizes a Long Short-Term Memory neural network and the Grasshopper Optimization Algorithm. The framework aims to improve the detection of PD while ensuring accurate and efficient classification of speech-based signals. …”
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On the machine learning algorithm combined evolutionary optimization to understand different tool designs’ wear mechanisms and other machinability metrics during dry turning of D2... by Muhammad Sana, Muhammad Umar Farooq, Sana Hassan, Anamta Khan

“…In this study, three-step novel modelling approach for optimal prediction of dry turning parameters is proposed. …”
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Few-shot hotel industry site selection prediction method based on meta learning algorithms and transportation accessibility by Na Li, Huaishi Wu

“…Abstract Exploring the rationality of hotel location selection is of significant importance for optimizing urban spatial structure and improving tourism service levels. …”
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Short-Term Power Load Forecasting Using Adaptive Mode Decomposition and Improved Least Squares Support Vector Machine by Wenjie Guo, Jie Liu, Jun Ma, Zheng Lan

“…Different frequency features are effectively extracted by using the proposed combination kernel structure, which can achieve the balance of learning capacity and generalization capacity for each unique load component. Further, an optimized genetic algorithm is deployed to optimize model parameters in ILSSVM by integrating the adaptive genetic algorithm and simulated annealing to improve load forecasting accuracy. …”
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Predicting equilibrium scour depth around non-circular bridge piers with shallow foundations using hybrid explainable machine learning methods by Nasrin Eini, Saeid Janizadeh, Sayed M. Bateni, Changhyun Jun, Essam Heggy, Marek Kirs

“…This study combines two metaheuristic optimization techniques—Siberian tiger optimization (STO) and brown-bear optimization algorithms (BOA)—with artificial neural networks (ANNs) to enhance deq prediction accuracy for both round- and sharp-nosed piers using both field and laboratory data. …”
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Optimizing Transportation Costs: Enhancing Logistics Efficiency and Resource Utilization in Dynamic Environments by Cao Ngoc Anh, Tran Bich Thao, Tran Ba Hung, Trinh Thu Huong, Nguyen Viet Hung

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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…The GJO algorithm fine-tunes the hyperparameters of MARL to improve generalization across different WSN configurations. …”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…The superiority of the proposed model (XGB-MPA) compared to two other hybrid models, including XGB-PSO (Particle Swarm Optimization) and XGB-GWO (Grey Wolf Optimization) was also investigated. …”
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UAV Path Planners in Complex Environments: A Multi-Dimensional Perturbation Based on Artificial Bee Colony by Xuzhao Chai, Guanhao Zhou, Haoyu Wang, Ping Liu, Zhongyun Liu, Chao Li, Li Yan

“…In the onlooker bee phase, the curvature-guided elite neighbor search strategy is used to prioritizes high-curvature waypoints, enhancing optimization efficiency in complex terrain. Furthermore, path costs are independently modeled in the horizontal and vertical directions. …”
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Program Scheduling With Multi-Skill and External Resource Coordination Consideration Using Improved NSGA-II: Case Study by Heng Zhang, Jingbo Zhou, Huaying Ruan, Yixuan Qin

“…A case study was then developed based on the R program of technology-driven company S. The allocation model was solved using both the classic and improved versions of the algorithm. …”
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Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods by Babak Pourakbari, Setareh Mamishi, Sepideh Keshavarz Valian, Shima Mahmoudi, Reihaneh Hosseinpour Sadeghi, Mohammad Reza Abdolsalehi, Mahmoud Khodabandeh, Mohammad Farahmand

“…Integrating these predictive models into clinical practice could support early identification of high-risk patients and optimize clinical decision-making.…”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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A Novel High-Precision Workpiece Self-Positioning Method for Improving the Convergence Ratio of Optical Components in Magnetorheological Finishing by Yiang Zhang, Pengxiang Wang, Chaoliang Guan, Meng Liu, Xiaoqiang Peng, Hao Hu

“…A composite data acquisition method using both a camera and probe is designed, and a stepwise global optimization model is constructed by integrating a synchronous iterative localization algorithm with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). …”
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SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks by Sneh Pandya, Purvik Patel, Brian D Nord, Mike Walmsley, Aleksandra Ćiprijanović

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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification by Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Lu Peng, Fahdah Almarshad

“…In this study, we introduced XNANet, a self-attention-based CNN network for image classification. Bayesian optimization has been used to initialize the hyperparameters of the proposed model to improve training on the radiographic images. …”
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Research on Multi-Objective Coordinated Planning of Distribution Networks Based on Improved Generative Adversarial Networks by Li Zhu

“…This paper addresses the significant challenges that the uncertainty of renewable energy (RE) outputs, such as wind and solar power, bring to distribution network planning and operation by proposing a multi-objective bi-level distribution network planning model based on an improved generative adversarial network and carbon footprint analysis. …”
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Application of the Bidirectional Encoder Representations from Transformers Model for Predicting the Abbreviated Injury Scale in Patients with Trauma: Algorithm Development and Vali... by Jun Tang, Yang Li, Keyu Luo, Jiangyuan Lai, Xiang Yin, Dongdong Wu

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Research on Performance Predictive Model and Parameter Optimization of Pneumatic Drum Seed Metering Device Based on Backpropagation Neural Network by Yilong Pan, Yaxin Yu, Junwei Zhou, Wenbing Qin, Qiang Wang, Yinghao Wang

“…The MOPSO algorithm uses the BPNN predictive model as a fitness function to search for the optimal solution for three types of seeds, and the optimized results were verified through bench experiments. …”
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Research on bearing fault diagnosis based on ISA-VMD and IMSE by Feng Yan

“…This method leverages an improved sparrow search algorithm (ISSA) to optimize the variational mode decomposition (VMD) method and employs an improved multiscale sample entropy (IMSE) for fault feature extraction. …”
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Transformer Fault Diagnosis Utilizing Feature Extraction and Ensemble Learning Model by Gonglin Xu, Mei Zhang, Wanli Chen, Zhihui Wang

“…The final step involves optimizing the Light Gradient Boosting Machine (LightGBM) model using IAOS algorithm for transformer fault classification; this model is an ensemble learning model. …”
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