Adaptable Reduced-Complexity Approach Based on State Vector Machine for Identification of Criminal Activists on Social Media by Imran Shafi, Sadia Din, Zahid Hussain, Imran Ashraf, Gyu Sang Choi

“…This study proposes simplified yet adaptable framework that uses a novel features extraction algorithm for extracting features from the textual part of social media contents. …”
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Modification of the WaldBoost algorithm to improve the efficiency of solving pattern recognition problems in real-time by A. N. Chesalin, S. Ya. Grodzenskiy, M. Yu. Nilov, A. N. Agafonov

“…We consider the implementation of the WaldBoost algorithm, which combines two algorithms: adaptive boosting of weak classifiers – AdaBoost (adaptive boosting), which has a high generalizing ability, and the sequential probability ratio test – SPRT (Wald test), which is the optimal rule of decision-making when distinguishing two hypotheses. …”
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Internet intelligent routing architecture and algorithm by Fei GUI, Yang CHENG, Dan LI, Sihong HONG

“…To address this problem in a practical and efficient approach, a novel intelligent routing algorithm based on machine learning (ML) was proposed. …”
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Automated Detection of Poor-Quality Scintigraphic Images Using Machine Learning by Anil K. Pandey, Akshima Sharma, Param D. Sharma, Chandra S. Bal, Rakesh Kumar

“…These 32 feature vectors of each image were used for the classification of images into poor or good quality using machine learning algorithm (multivariate adaptive regression splines [MARS]). …”
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Utility of Domain Adaptation for Biomass Yield Forecasting by Jonathan M. Vance, Bryan Smith, Abhishek Cherukuru, Khaled Rasheed, Ali Missaoui, John A. Miller, Frederick Maier, Hamid Arabnia

“…Previous work used machine learning (ML) to estimate past and current alfalfa yields and showed that domain adaptation (DA) with data synthesis shows promise in classifying yields as high, medium, or low. …”
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A Comprehensive Review and Benchmarking of Fairness-Aware Variants of Machine Learning Models by George Raftopoulos, Nikos Fazakis, Gregory Davrazos, Sotiris Kotsiantis

“…We analyze these adaptations in terms of their methodological adjustments, impact on algorithmic bias and ability to maintain predictive performance comparable to the original models.…”
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Accelerating Fair Federated Learning: Adaptive Federated Adam by Li Ju, Tianru Zhang, Salman Toor, Andreas Hellander

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Predicting regional tau accumulation with machine learning‐based tau‐PET and advanced radiomics by Saima Rathore, Ixavier A. Higgins, Jian Wang, Ian A. Kennedy, Leonardo Iaccarino, Samantha C. Burnham, Michael J. Pontecorvo, Sergey Shcherbinin

“…We trained an AdaBoost machine learning algorithm in a 2:1 split train‐test configuration to derive a prognostic index that (i) stratifies individualized brain regions including global (AD‐signature region) and lobar regions (frontal, occipital, parietal, temporal) into stable/slow‐ and fast‐progressors based on future tau accumulation, and (ii) forecasts individualized regional annualized‐rate‐of‐change in flortaucipir‐PET SUVr. …”
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Dynamic neutrosophic cognitive map with improved cuckoo search algorithm (DNCM-ICSA) and ensemble classifier for rheumatoid arthritis (RA) disease by B. Chithra, R. Nedunchezhian

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A Comparative Study of Machine Learning Algorithms for Intrusion Detection Systems using the NSL-KDD Dataset by Rulyansyah Permata Putra, Amarudin Amarudin

“…The primary objective of this study is to design and implement a machine learning model for detecting network intrusions efficiently while minimizing latency, through a comparative analysis of several algorithms: Decision Tree, Random Forest, Support Vector Machine (SVM), and Boosting. …”
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Identification of Plasma Proteins Associated with Alzheimer's Disease Using Feature Selection Techniques and Machine Learning Algorithms by Zakaria Mokadem, Mohamed Djerioui, Bilal Attallah, Youcef Brik

“…The SBFS technique generated all possible combinations of protein groups from the 146 proteins, which were then trained and tested using five machine learning models: Decision Tree, Random Forest, Extremely Randomized Trees, Extreme Gradient Boosting, and Adaptive Boosting. …”
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Adversarial sample generation algorithm for vertical federated learning by Xiaolin CHEN, Daoguang ZAN, Bingchao WU, Bei GUAN, Yongji WANG

“…To adapt to the scenario characteristics of vertical federated learning (VFL) applications regarding high communication cost, fast model iteration, and decentralized data storage, a generalized adversarial sample generation algorithm named VFL-GASG was proposed.Specifically, an adversarial sample generation framework was constructed for the VFL architecture.A white-box adversarial attack in the VFL was implemented by extending the centralized machine learning adversarial sample generation algorithm with different policies such as L-BFGS, FGSM, and C＆amp;W.By introducing deep convolutional generative adversarial network (DCGAN), an adversarial sample generation algorithm named VFL-GASG was designed to address the problem of universality in the generation of adversarial perturbations.Hidden layer vectors were utilized as local prior knowledge to train the adversarial perturbation generation model, and through a series of convolution-deconvolution network layers, finely crafted adversarial perturbations were produced.Experiments show that VFL-GASG can maintain a high attack success while achieving a higher generation efficiency, robustness, and generalization ability than the baseline algorithm, and further verify the impact of relevant settings for adversarial attacks.…”
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A Machine Learning-Based Novel Energy Optimization Algorithm in a Photovoltaic Solar Power System by Kalapala Prasad, J. Samson Isaac, P. Ponsudha, N. Nithya, Santaji Krishna Shinde, S. Raja Gopal, Atul Sarojwal, K. Karthikumar, Kibrom Menasbo Hadish

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Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city by Xuechun Zhou, Xiaofei Zou, Wenzuixiong Xiong

“…Adopting a healthy city development perspective, the research aims to assess the impact of green space optimization on urban health, economic performance, and social structure.MethodsA multivariable model was constructed using random forest and Support Vector Machine (SVM) algorithms to evaluate the influence of key indicators on urban green space. …”
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Integrating Bioengineering and Machine Learning: A Multi-Algorithm Approach to Enhance Agricultural Sustainability and Resource Efficiency by Senthil G.A., Prabha R., Asha R.M., Suganthi S.U., Sridevi S.

“…The novel research incorporates high-level machine learning algorithms for optimizing agricultural performance regarding sustainability and resource efficiencies. …”
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Estimating Tea Plant Physiological Parameters Using Unmanned Aerial Vehicle Imagery and Machine Learning Algorithms by Zhong-Han Zhuang, Hui-Ping Tsai, Chung-I Chen

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Estimating Economic Insights: A Machine Learning Method for Estimating the Shanghai Stock Exchange by Reza Seifi Majdar, Seyed Hadi Seyed Hatami

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A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting by Aleksei Vakhnin, Ivan Ryzhikov, Harri Niska, Mikko Kolehmainen

“…The hybrid MO evolutionary algorithm integrates elements of genetic algorithms and self-adapted differential evolution. …”
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CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…To address this problem, this paper proposes a feature extraction method based on the combination of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Fuzzy Entropy (FN). Due to the slow convergence speed and the tendency to fall into local optimal solutions of the Hippopotamus Optimization Algorithm (HO), an improved Hippopotamus Optimization (IHO) algorithm-optimized Support Vector Machine (SVM) model for valve leakage diagnosis is introduced to further enhance the accuracy of valve leakage diagnosis. …”
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A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats by Dheyaaldin Alsalman

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