Torque ripple reduction and increasing of torque per volume for hybrid electrical vehicle by A. Hosseinpour

“…In this paper series hybrid excitation synchronous machine (SHESM) is utilized as HEV. Two-objective optimization problems are solved by MOEA/D, NSGA II, PESA II and SPEA II algorithms based on a two-dimensional (2-D) model. …”
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Mitigating malicious denial of wallet attack using attribute reduction with deep learning approach for serverless computing on next generation applications by Amal K. Alkhalifa, Mohammed Aljebreen, Rakan Alanazi, Nazir Ahmad, Sultan Alahmari, Othman Alrusaini, Ali Alqazzaz, Hassan Alkhiri

“…Furthermore, the feature selection process-based cuckoo search optimization (CSO) model efficiently identifies the most impactful attributes related to potential malicious activity. …”
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Focused Crawler for Event Detection Using Metaheuristic Algorithms and Knowledge Extraction by Hossein Moradi, Fatemeh Azimzadeh

“…Comparative analysis reveals that the proposed method outperformed alternative models. Nevertheless, when tested across various data models and datasets, the WOA model consistently demonstrated superior performance, albeit exhibiting reduced evaluation metrics for Wikipedia text data.…”
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Comparative analysis of heart disease prediction using logistic regression, SVM, KNN, and random forest with cross-validation for improved accuracy by Yagyanath Rimal, Navneet Sharma, Siddhartha Paudel, Abeer Alsadoon, Madhav Parsad Koirala, Sumeet Gill

“…Conversely, the logistic regression model exhibited the lowest accuracy of 84% among the four machine learning models. …”
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Leveraging a foundation model zoo for cell similarity search in oncological microscopy across devices by Gabriel Kalweit, Gabriel Kalweit, Anusha Klett, Paula Silvestrini, Paula Silvestrini, Jens Rahnfeld, Jens Rahnfeld, Mehdi Naouar, Mehdi Naouar, Yannick Vogt, Yannick Vogt, Diana Infante, Diana Infante, Rebecca Berger, Jesús Duque-Afonso, Tanja Nicole Hartmann, Marie Follo, Marie Follo, Elitsa Bodurova-Spassova, Elitsa Bodurova-Spassova, Michael Lübbert, Michael Lübbert, Roland Mertelsmann, Roland Mertelsmann, Roland Mertelsmann, Joschka Boedecker, Joschka Boedecker, Joschka Boedecker, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Maria Kalweit, Maria Kalweit

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Improved Deviation Sparse Fuzzy C-Means-2D Cumulative Sum Average Filter and Modified Sine Cosine Crow Search Algorithm-Wavelet Extreme Learning Machine for Brain Tumor Detection a... by Suvashisa Dash, Satyasis Mishra, Mohammed Siddique, Demissie J. Gelmecha, Ram Sewak Singh

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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

“…These features serve as inputs for training the proposed IGPR model, followed by random sample testing. The IGPR model incorporates hyperparameter tuning of Gaussian process regression using Bayesian optimization. …”
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Dynamic reconstruction of electroencephalogram data using RBF neural networks by Xuan Wang, Congcong Du, Xianjin Ke, Jian Zhang, Zheng Zheng, Yayan Yue, Ming Yu

“…Signals were preprocessed through bandpass filtering (1–35 Hz) and Independent Component Analysis (ICA) for artifact removal. neural network was trained on EEG time-series data with PSO employed to optimize model parameters identify fixed points in the reconstructed neural system. …”
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Study on the correlation between rail station area vitality and built environment by Wangyang Gui, Wenli Wu, Di Wu

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Fast Multimodal Trajectory Prediction for Vehicles Based on Multimodal Information Fusion by Likun Ge, Shuting Wang, Guangqi Wang

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An Overview of Deep Neural Networks for Few-Shot Learning by Juan Zhao, Lili Kong, Jiancheng Lv

“…We categorize FSL methods into three types based on strategies to increase labeled samples or reduce hypothesis space: data augmentation, model-based methods, and algorithm-optimized approaches. …”
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Advances in Numerical Modeling for Heat Transfer and Thermal Management: A Review of Computational Approaches and Environmental Impacts by Łukasz Łach, Dmytro Svyetlichnyy

“…Additionally, the increasing energy consumption in numerical modeling highlights the need for optimization strategies to mitigate environmental impact. …”
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Enhancing public transportation through user feedback: the case of Braamfontein, Johannesburg by Retsepile Kalaoane, Trynos Gumbo

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Integrating hybrid bald eagle crow search algorithm and deep learning for enhanced malicious node detection in secure distributed systems by Feras Mohammed Al-Matarneh

“…Meanwhile, the convolutional sparse autoencoder (CSAE) model detects malicious nodes. Finally, the dung beetle optimization (DBO) method is employed for the parameter range of the CSAE method. …”
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Future flood susceptibility mapping under climate and land use change by Hamidreza Khodaei, Farzin Nasiri Saleh, Afsaneh Nobakht Dalir, Erfan Zarei

“…This research aims to develop flood susceptibility maps considering the impacts of climate change and land use changes, providing insights into risks from urbanization and climate shifts. Three machine learning models—XGBoost, Random Forest (RF), and Support Vector Machine (SVM)—optimized with Particle Swarm Optimization, were applied to the flood-prone Kashkan watershed in Iran. …”
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Diverse Counterfactual Explanations (DiCE) Role in Improving Sales and e-Commerce Strategies by Simona-Vasilica Oprea, Adela Bâra

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Faster Convergence With Less Communication: Broadcast-Based Subgraph Sampling for Decentralized Learning Over Wireless Networks by Daniel Perez Herrera, Zheng Chen, Erik G. Larsson

“…Decentralized stochastic gradient descent (D-SGD) is a widely adopted optimization algorithm for decentralized training of machine learning models across networked agents. …”
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An Automated Framework of Superpixels-Saliency Map and Gated Recurrent Unit Deep Convolutional Neural Network for Land Cover and Crops Disease Classification by Irfan Haider, Muhammad Attique Khan, Muhammad Nazir, Saleha Masood, Naoufel Kraiem, Dina Abdulaziz Alhammadi

“…In the second phase, EfficientNet-b0 architecture is fine-tuned with hyperparameters optimized via Bayesian Optimization. Also, the fine-tuned model is embedded with a single self-attention residual block fused with an efficient average pool layer. …”
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Traffic Incident Clearance Time Prediction and Influencing Factor Analysis Using Extreme Gradient Boosting Model by Jinjun Tang, Lanlan Zheng, Chunyang Han, Fang Liu, Jianming Cai

“…The XGBoost is built for each cluster. Bayesian optimization is used to optimize the parameters of XGBoost, and the MAPE is considered as the predictive indicator to evaluate the prediction performance. …”
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State of Health Estimation of Lithium-Ion Batteries Using Fusion Health Indicator by PSO-ELM Model by Jun Chen, Yan Liu, Jun Yong, Cheng Yang, Liqin Yan, Yanping Zheng

“…This paper presents a novel SOH estimation method that integrates Particle Swarm Optimization (PSO) with an Extreme Learning Machine (ELM) to improve prediction accuracy. …”
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