Traffic weaver: Semi-synthetic time-varying traffic generator based on averaged time series by Piotr Lechowicz, Aleksandra Knapińska, Adam Włodarczyk, Krzysztof Walkowiak

“…The primary motivation behind Traffic Weaver is to furnish semi-synthetic time-varying traffic in telecommunication networks, facilitating the development and validation of traffic prediction models, as well as aiding in the deployment of network optimization algorithms tailored for time-varying traffic.…”
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Structural integrity and hybrid ANFIS-PSO modeling of the corrosion rate of ductile irons in different environments by Ukoba K., Akinribide O.J., Adeleke O.

“…The percentage error of the ANFIS-PSO predictions is significantly lower than the ANFIS-standalone prediction. …”
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Drosophila Eye Gene Regulatory Network Inference Using BioGRNsemble: An Ensemble-of-Ensembles Machine Learning Approach by Abdul Jawad Mohammed, Amal Khalifa

“…Our validation analysis using the TFLink online database yielded 3703 verified predicted gene links, out of 534,843 predictions. Conclusion: Although the BioGRNsemble approach presents a promising method for inferring smaller, focused regulatory networks, it encounters challenges related to algorithm sensitivity, prediction bias, validation difficulties, and the potential exclusion of broader regulatory interactions. …”
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Klasifikasi Metode Data Mining untuk Prediksi Kelulusan Tepat Waktu Mahasiswa dengan Algoritma Naïve Bayes, Random Forest, Support Vector Machine (SVM) dan Artificial Neural Nerwor... by Satrio Junaidi, Rani Valicia Anggela, Delsi Kariman

“…So, to deal with this problem, data mining classification is carried out to predict student graduation on time to find patterns for student on-time graduation predictions. …”
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MSASGCN :  Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting by Yang Cao, Detian Liu, Qizheng Yin, Fei Xue, Hengliang Tang

“…Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. …”
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An Adaptive Motion Estimation Scheme for Video Coding by Pengyu Liu, Yuan Gao, Kebin Jia

“…Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. …”
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Machine Learning Application for Improving Customer and Postal Logistics Operator Satisfaction in Urban Areas – A Review by Adisa MEDIĆ, Amel KOSOVAC, Ermin MUHAREMOVIĆ, Muhamed BEGOVIĆ

“…Machine learning (ML) is a crucial component of artificial intelligence that has recently attracted attention for its application in logistics. ML algorithms are used on large datasets. They create logic correlations among given data and provide predictions of specific values. …”
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A comparative artificial neural networks for Schwarzschild black hole (SBH) radius by Khalil Ur Rehman, Wasfi Shatanawi, Weam G. Alharbi

“…Two various training functions namely Levenberg-Marquardt training algorithm (LMTA) and Scaled Conjugate Gradient training algorithms (SCGTA) are used. …”
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Effects of neighborhood streetscape on the single-family housing price: Focusing on nonlinear and interaction effects using interpretable machine learning. by Jaewon Han, Ayoung Woo, Sugie Lee

“…Previous studies using the conventional Hedonic Price Model to predict existing housing prices may have limitations in addressing the relationship between house prices and streetscapes as visually perceived at the human eye level, due to the constraints of streetscape estimations. …”
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AI Methods for New Psychoactive Substance (NPS) Design and Analysis by Enrico Greco

“…Special emphasis is placed on mass spectrometry (MS)-based techniques, where AI algorithms (e.g., for spectral prediction and pattern recognition) are revolutionizing the detection and characterization of unknown NPSs. …”
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MEAT TRADE DYNAMICS: MONTHLY PATTERNS IN ROMANIA’S IMPORTS (CMA AND HOLT-WINTERS METHODS) by Aurelia Vasilica BĂLAN, Elena TOMA

“…The analysis aims to project the values of meat imports until May 2025 by using various forecasting algorithms to understand import trends and seasonality. …”
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Automatic evaluation and optimization of map registration based on feature overlap area ratio by Jiqiu Deng, Xiaoyan Chen, Dong Zhang

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Performances Comparison for a Rotating Shaft Suspended by 4-Axis Radial Active Magnetic Bearings via 𝜇-Synthesis, Loop-Shaping Design, and Sub(𝐻)∞with Uncertainties by G. Barbaraci, G. Virzi' Mariotti

“…The first controller implemented for this purpose is PID controller that is characterized by an algorithm that leads the amplifier to produce control current until the operating point condition is not reached, this is obtained by an integration operator. …”
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Fault Diagnosis and Prognosis With Inferential Sensors: A Hybrid Approach Integrating Symbolic Regression and Information Theory by Efi Safikou, Krishna R. Pattipati, George M. Bollas

“…We propose a fault diagnosis approach that integrates symbolic regression and information theory to optimize inferential sensors, which, along with traditional detection techniques and hard sensors, contribute to a comprehensive fault detection and diagnosis algorithm. Additionally, we introduce an advanced predictive scheme to estimate time-dependent fault evolution functions that enable us to compute the remaining useful life (RUL) of the system. …”
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Modified Traffic Flow Model with Connected Vehicle Microscopic Data for Proactive Variable Speed Limit Control by Jie Fang, Huixuan Ye, Said M. Easa

“…The proposed VSL control algorithm adopts the Model Predictive Control (MPC) framework, which employs a modified version of the classic traffic flow model METANET to take advantage of the microscopic data in traffic flow predictions. …”
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Accurate Solar Radiation Forecasting Through Feature-Enhanced Decision Trees and Wavelet Decomposition by Gaizen Soufiane, Abbou Ahmed, Fadi Ouafia

“…This study explores the efficacy of the decision tree algorithm in predicting solar power generation, addressing the inherent variability in photovoltaic (PV) energy production due to weather conditions. …”
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Hybrid solver with deep learning for transport problem in porous media by Vladislav Trifonov, Egor Illarionov, Anton Voskresenskii, Musheg Petrosyants, Klemens Katterbauer

“…Extensive experiments with dynamic and static reservoir features revealed that improving predictive accuracy does not necessarily improve fluid modeling. …”
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FUNCTIONING OF THE CAR PARKING PLACES NEAR HOUSES: FORMULATION OF THE PROBLEM OF THE ROAD CITY NETWORK by I. E. Agureev, D. A. Yurchenko

“…The basis of the research was the development in the field of predictive simulation of automobile transport systems. …”
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Multi-Agent System for Emulating Personality Traits Using Deep Reinforcement Learning by Georgios Liapis, Ioannis Vlahavas

“…Conventional personality assessment methods depend on subjective input, while game-based AI predictive methods offer a dynamic and objective framework. …”
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Analysis of crop disease and pest occurrences: Insights from Japan's national surveys. by Jianqiang Sun, Sunao Ochi, Takehiko Yamanaka

“…However, the prediction error remained substantial, with an RMSE of 6.2 ± 19.6. …”
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