Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller by Vineet Kumar, Vineet Kumar, Ark Dev

Subjects: “…Harris hawks optimization algorithm…”
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A spherical fuzzy WASPAS approach to prioritize the factors enhancing the effectiveness of physical education classroom teaching by Yuhan Gao, Ali Yu

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Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

“…Therefore, the Test Suite Reduction (TSR) process is of great importance, contributing to the reduction of time and costs in executing test suites for complex software by minimizing the number of test cases to be executed. …”
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Validation of a deep learning–based AI system for HER2-targeted breast cancer assessment using ultrasound imaging in a clinical setting by Kathryn Malherbe

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Improving Moth-Flame Optimization Algorithm by using Slime-Mould Algorithm by Sami N. Hussein, Nazar K. Hussein

“…The two predicted new algorithms were tested with standard test functions and the results were encouraging compared to the standard algorithms. …”
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Strength prediction and failure mode classification for SRC shear beams using GA-BP ANN method by Gangfeng Yao, Bingyi Li

“…Considering the advantages of machine-learning (ML) approaches, the back-propagation (BP) artificial neural network (ANN) method combined with genetic algorithm (GA) was employed to the prediction of strength and failure mode of SRC shear beams. …”
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Enhancing the prediction of vitamin D deficiency levels using an integrated approach of deep learning and evolutionary computing by Ahmed Alzahrani, Muhammad Zubair Asghar

“…Specifically, we employ a hybrid deep learning model that includes convolutional neural networks (CNN) and bidirectional long short-term memory (BiLSTM) networks to predict VDD data effectively. To improve the models effectiveness and guarantee the optimal choice of the features and hyper-parameters, we incorporate evolutionary computing methods, particularly genetic algorithms (GA). …”
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RSA modulus length regression prediction based on the Run Test and machine learning in the ciphertext-only scenarios by Ke Yuan, Chenmeng Zhao, Longwei Yang, Hanlin Sun, Sufang Zhou, Chunfu Jia

“…Abstract RSA is a classical public key cryptographic algorithm, over 40 years of widespread use has proven that its security is reliable when the key parameters are properly configured. …”
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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials by Simin Nazari, Amira Abdelrasoul

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Prediction of maximum forming depth in single point incremental forming of 6061 aluminum alloy based on Adaboost regression by LIANG Zhikai, ZHANG Zhichao, HU Lan, PANG Qiu

“…Based on the experimental results， a regression model using the Adaboost algorithm is developed to predict the forming depth of 6061 aluminum alloy thin sheets at the forming diameter of 100 mm. …”
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Re-Imagining a 'We' Beyond the Gathering of Reductions by Lila Athanasiadou, Goda Klumbyte, Antoinette Rouvroy

“…Lastly, within the mental ecology, Rouvroy reconceptualizes the legal subject as a performance that operates within the proliferation of asignifying data signs, reimagining a “we” beyond the gathering of reductions.    …”
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Research on POI quality prediction based on KPCA-GA-BP neural network by Lu LIU, Dan YANG, Ruijie CHEN, Jia LI, Xi ZHOU

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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Several peak-to-average power ratio (PAPR) reduction methods have been used in orthogonal frequency division multiplexing (OFDM) applications. …”
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Predictive modeling of asthma drug properties using machine learning and topological indices in a MATLAB based QSPR study by Jalal Hatem Hussein Bayati, Abid Mahboob, Laiba Amin, Muhammad Waheed Rasheed, Abdu Alameri

“…This study utilizes MATLAB program-based algorithms to calculate topological indices and machine learning algorithms to explore their ability to predict the physio-chemical properties of asthma drugs. …”
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An improved deep learning model for soybean future price prediction with hybrid data preprocessing strategy by Dingya CHEN, Hui LIU, Yanfei LI, Zhu DUAN

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Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outcomes by Xiaonan Zhang, Li Li, Xiaoyu Shi, Yunxia Zhao, Zhaogen Cai, Ni Ni, Di Yang, Zixin Meng, Xu Gao, Li Huang, Tao Wang

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Comparison of Different Heuristics Integrated with Neural Networks: A Case Study for Earthquake Damage Estimation by Ayşe Berika Varol Malkoçoğlu, Zeynep Orman, Rüya Şamlı

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Research on optimal selection of runoff prediction models based on coupled machine learning methods by Xing Wei, Mengen Chen, Yulin Zhou, Jianhua Zou, Libo Ran, Ruibo Shi

Subjects: “…Runoff prediction…”
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Hyperband-Optimized CNN-BiLSTM with Attention Mechanism for Corporate Financial Distress Prediction by Yingying Song, Monchaya Chiangpradit, Piyapatr Busababodhin

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A Machine Learning Approach to Predict Site Selection from the Perspective of Vitality Improvement by Bin Zhao, Hao Zheng, Xuesong Cheng

“…To enhance site selection and planning efficiency, we developed a predictive model integrating Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs). …”
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