An Optimized Hybrid PSO-ELM for Parkinson’s Disease Diagnosis by Gunakala Archana, Afzal Hussain Shahid

“…This paper employs three feature ranking algorithms, namely ReliefF, minimum Redundancy Maximum relevance (mRMR), and Fisher, on six publicly available PD datasets. …”
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Growth Rates of  Morphometric Variables in Approximately Linear Sections Using Lines in R3 by Aquiles E. Darghan, Enrique Quevedo García, Sergio Esteban Gamboa Muñoz, Carlos Armando Rivera Moreno

“…In this research, different classification algorithms are applied to select the approximately linear phase present in various nonlinear models of variables or parameters used in the modeling of the growth of a crop. …”
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Optimizing adaptability and rational control strategies for cyclogyro systems by Sibei Wei

“…The proposed approach integrates mathematical modeling, optimization algorithms, real-time data analysis, and feedback mechanisms to predict and adjust the system behavior. …”
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The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This study aims to classify high-growth firms using several machine learning algorithms, including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) Regularization, XGBoost, Gradient Descent, Naive Bayes and Random Forest. …”
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Methodology for Deriving Parameters for Optimization Models of Systems of Flexible Energy Resources by Lukas Peter Wagner, Alexander Fay

“…This methodology includes algorithms for determining operational boundaries, the input–output relationship, system states, and parameters for storage systems. …”
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Multisegment Mapping Network for Massive MIMO Detection by Yongzhi Yu, Jianming Wang, Limin Guo

“…Because of the large number of massive MIMO antennas, the computational complexity of detection has increased significantly, which poses a significant challenge to traditional detection algorithms. However, the use of deep learning for massive MIMO detection can achieve a high degree of computational parallelism, and deep learning constitutes an important technical approach for solving the signal detection problem. …”
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PULSim: User-Based Adaptable Simulation Tool for Railway Planning and Operations by Yong Cui, Ullrich Martin, Jiajian Liang

“…Users and researchers gain the ability to rapidly develop their own algorithms, supported by the tailored simulation process in a flexible manner. …”
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Role of Customs Legislation and Practice of Its Implementation in the Protection of Fauna of Ukraine by I. O Panov

“…The author has emphasized the need to develop automated algorithms for the exchange of information on the movement of wild animals across the border between the relevant government agencies in order to further control the legality of the origin of animals and bring to justice those who illegally released wild animals. …”
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Predictive Analytics in Finance Using the Arima Model. Application for Bucharest Stock Exchange Financial Companies Closing Prices by Spulbar Cristi, Ene Cezar Cătălin

“…Moreover, the selected model is part of the time series analysis under prediction algorithms, the purpose of the research being to predict the prices of the selected shares. …”
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Data Clustering for Sentiment Classification with Naïve Bayes and Support Vector Machine by Bayu Yanuargi, Ema Utami, Kusrini, Arli Aditya Parikesit

“…Clustering helps improve sentiment classification, making it more targeted and allowing a comparison of two machine learning algorithms: Naïve Bayes and Support Vector Machine (SVM). …”
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Application of big data technology in enterprise information security management by Ping Li, Limin Zhang

“…A big data analysis system that can monitor and intelligently identify potential security risks in real-time is constructed by designing complex network analysis algorithms and machine learning models. For different types of security threats, the system uses feature engineering and model training processes to extract key risk indicators and optimize model prediction performance. …”
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Deep learning–based resource allocation for secure transmission in a non-orthogonal multiple access network by Miao Zhang, Yao Zhang, Qian Cen, Shixun Wu

“…Machine learning techniques, especially deep learning algorithms have been widely utilized to deal with different kinds of research problems in wireless communications. …”
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Integrating Satellite Data and In-situ Observations for Trophic State Assessment of Renuka Lake, Himachal Pradesh, India by Sujit Kumar Jally, Rakesh Kumar and Sibabrata Das

“…The present study focuses on estimating the Trophic State Index (TSI) of Renuka Lake, the smallest Ramsar site in India, utilizing in-situ observed Secchi disk transparency (SDT) and satellite data. Site-specific algorithms were developed by establishing the relationship between the spectral band ratio of Landsat 8 OLI and LISS-III with that of in-situ measured SDT data. …”
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Development and evaluation of a low-cost database solution for the Community Paramedicine at Clinic (CP@clinic) database. by Ricardo Angeles, Krzysztof Adamczyk, Francine Marzanek, Melissa Pirrie, Mikayla Plishka, Gina Agarwal

“…This low-cost, user-friendly and secure database captures initial and follow-up data, incorporates algorithms that guide the paramedics, and calculates risk factor scores for the participants. …”
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Investigating Pre-service Chemistry Teachers’ Problem Solving Strategies: Towards Developing a Framework in Teaching Stoichiometry by Allen A. Espinosa, Rebecca C. Nueva España, Arlyne C. Marasigan

“…The study found out that the most prominent strategy among pre-service chemistry teachers is the mole method, which is algorithmic by nature. Very few of them used the proportionality method and none made use of the logical method. …”
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Stock price prediction using the Sand Cat Swarm Optimization and an improved deep Long Short Term Memory network by Burak Gülmez

“…The research evaluates multiple algorithms including ANN, LSTM variants, Auto-ARIMA, Gradient Boosted Trees, DeepAR, N-BEATS, N-HITS, and the proposed LSTM-SCSO using DAX index data from 2018 to 2023. …”
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Identification of hub genes and pathogenesis in Kawasaki disease based on bioinformatics analysis by Min Cao, Zhenhu Zhang, Qian Liu, Yuda Zhang

“…Materials and Methods: Gene Expression Omnibus (GEO) datasets GSE68004 and GSE73461 were downloaded, and the differentially expressed genes (DGEs) were taken, along with DEGs enrichment analysis and protein interaction network. Finally, five algorithms in CytoHubba plug-in were applied to obtain hub genes. …”
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Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence by Tu T. Nguyen, Hoa Pham Duy, Tung Pham Thanh, Hoang Hiep Vu

“…Various AI models were developed with different training algorithms and a number of nodes in the hidden layer to obtain the optimal model for the FRHSSCC data. …”
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Intellectual measurement and evaluation of the results of customs authorities’ activities by G. I. Goremykina, Yu. E. Gupanova

“…The study is based on a cognitive approach that allows describing the intellectual environment of customs authorities and models of evaluation and management based on fuzzy logic algorithms. The implementation of the technology for presenting experts’ knowledge in the subject area is carried out on the basis of constructing a prescriptive logical production model that allows formalizing expert knowledge in the form of implicative statements involving fuzzy formulations in antecedents and consequents, and using a generalized modus ponens as a logical conclusion. …”
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Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era. by Lathan Liou, Elizabeth Mostofsky, Laura Lehman, Soziema Salia, Francisco J Barrera, Ying Wei, Amal Cheema, Anuradha Lala, Andrew Beam, Murray A Mittleman

“…This study assessed seven statistical and machine learning algorithms-Lasso, Ridge, Elastic Net, Cox Gradient Boost, Extreme Gradient Boost Linear, Extreme Gradient Boost Tree, and Random Survival Forests in a post-policy cohort of 7,160 adult heart-only transplant recipients in the Scientific Registry of Transplant Recipients (SRTR) database who received their first transplant on or after October 18, 2018. …”
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