A Comparative Analysis of Machine Learning Algorithms in Energy Poverty Prediction by Elpida Kalfountzou, Lefkothea Papada, Christos Tourkolias, Sevastianos Mirasgedis, Dimitris Kaliampakos, Dimitris Damigos

“…The present paper adds new insights to the existing literature by exploring the capacity of ML algorithms to successfully predict energy poverty, as defined by different indicators, for the case of the “Urban Region of Athens” in Greece. …”
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Comparative Study for Classification Algorithms Performance in Crop Yields Prediction Systems by Halbast Rashid Ismael, Adnan Mohsin Abdulazeez, Dathar A. Hasan

“…Nowadays, data mining is an emerging research field in agriculture especially in the predicting and analysis of crop yield. This paper focuses on utilizing various data mining classification algorithms to predict the impact of various parameters such as area, season and production on the crop yield quality. …”
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Evolutionary algorithms for predicting aboveground carbon stocks in mopane woodlands in Mozambique by Severino José Macôo, Evandro Nunes Miranda, Lucas Rezende Gomide

“…Two evolutionary algorithms were tested: (1) a hybrid Genetic Algorithm and Random Forest (GARF), and (2) Genetic Programming (GP) using symbolic regression. …”
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad, Vaisali Chandrasekar, Omar Aboumarzouk, Ajay Vikram Singh, Sarada Prasad Dakua

“…The current study utilises state-of-the-art ML and DL models for predicting the hERG-blocking ability of chemical compounds using a dataset of 8337 molecules. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…One of those areas is the prediction and prevention of consumer churn. There are two basic types of consumer churn, complete churn and partial churn. …”
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Purchasing Prediction Using Machine Learning Algorithms for Optimizing Inventory Management by Reza Hamdi Prayetno, Rani Destika Purba, Kyrene Wirawan, Kelvin Sweet, Evta Indra

“…However, the challenges that companies often face are the uncertainty of market demand and changes in trends that are difficult to predict. Along with technological developments, traditional methods of inventory management are starting to be replaced by data-based approaches and machine learning algorithms. …”
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Predicting algorithm of attC site based on combination optimization strategy by Zhendong Liu, Xi Chen, Dongyan Li, Xinrong Lv, Mengying Qin, Ke Bai, Zhiqiang He, Yurong Yang, Xiaofeng Li, Qionghai Dai

“…Here, we design an attC site prediction algorithm based on a combination optimisation strategy. …”
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ALGORITHM FOR DETERMINATION OF PREDICTABLE SPECIALISTS’ NUMBER REQUIRED FOR STAFF RECRUITMENT AT ENTERPRISE by V. P. Goncharenko, D. N. Mironov, I. A. Rizhаnkov

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Fruit size prediction of tomato cultivars using machine learning algorithms by Masaaki Takahashi, Yasushi Kawasaki, Hiroki Naito, Hiroki Naito, Unseok Lee, Koichi Yoshi

“…We aimed to develop a method for early prediction of tomato fruit size at harvest with machine learning algorithm, and three machine learning models (Ridge Regression, Extra Tree Regrreion, CatBoost Regression) were compared using the PyCaret package for Python. …”
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Research on fusion algorithm for service life prediction based on kernel functions by TANG Huan, LI Yizhu, LYU Peng

“…However, as these devices approach the end of their lifecycle, a large amount of degradation data accumulates, allowing the degradation-data-based methods to yield more precise predictions. This paper proposes a kernel function-based fusion algorithm for service life prediction that combines predictions from both methods to enhance accuracy in predictions throughout the entire lifecycle. …”
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Scanning Micromirror Calibration Method Based on PSO-LSSVM Algorithm Prediction by Yan Liu, Xiang Cheng, Tingting Zhang, Yu Xu, Weijia Cai, Fengtian Han

“…The objective is to establish a correspondence between the actual deflection angle of the micromirror and the output of the measurement system employing a regression algorithm, thereby enabling the prediction of the tilt angle of the micromirror. …”
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Pose-Driven Body Shape Prediction Algorithm Based on the Conditional GAN by Jiwon Jang, Jiseong Byeon, Daewon Jung, Jihun Chang, Sekyoung Youm

“…To address these issues, we propose a lightweight algorithm that predicts body shape from clothed RGB images by leveraging pose estimation. …”
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Optimizing diabetes prediction with MLP neural networks and feature selection algorithm by Majd Mohammad A. Al-Hawamdeh

“… In this research, the goal was to improve diabetes prediction by combining Multilayer Perceptron Neural Network (MLPNN) with Memetic Algorithm (MA) and Arithmetic Optimization Algorithm (AOA). …”
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A Location Prediction Algorithm for Mobile Communications Using Directional Antennas by Xiaofeng Lu, Pietro Lio, Pan Hui, Haifei Jin

“…The authors validated the TRAC algorithm on some vehicles traces. The validation indicated that the algorithm efficiency of TRAC is larger than 96%. …”
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PERFORMANCE COMPARISON OF CLASSICAL ALGORITHMS AND DEEP NEURAL NETWORKS FOR TUBERCULOSIS PREDICTION by Gilgen Mate Landry, Rodolphe Nsimba Malumba, Fiston Chrisnovi Balanganayi Kabutakapua, Bopatriciat Boluma Mangata

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Algorithms for Effector Prediction in Plant Pathogens and Pests: Achievements and Current Challenges by César De los Santos-Briones, Karla Gisel Carreón-Anguiano, Sara E. Vila-Luna, Jewel Nicole Anna Todd, Ignacio Islas-Flores, Luis Sáenz-Carbonell, Pablo Alejandro Gamas-Trujillo, Blondy Canto-Canché

Subjects: “…algorithms…”
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Extreme Gradient Boosting Algorithm for Predicting Shear Strengths of Rockfill Materials by Mahmood Ahmad, Ramez A. Al-Mansob, Kazem Reza Kashyzadeh, Suraparb Keawsawasvong, Mohanad Muayad Sabri Sabri, Irfan Jamil, Arnold C. Alguno

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Machine learning algorithms to predict the tensile strength of novel composite materials by S. Sathees Kumar, P. Shyamala, Pravat Ranjan Pati

“…Five regression algorithms such as polynomial regression, bagging regression, random forest, XGBoost, and gradient boosting were trained and evaluated using five-fold cross-validation and standard error metrics. …”
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Differentially Private Clustered Federated Load Prediction Based on the Louvain Algorithm by Tingzhe Pan, Jue Hou, Xin Jin, Chao Li, Xinlei Cai, Xiaodong Zhou

“…The framework can train load-forecasting models with a fast convergence rate and better prediction performance than current mainstream federated learning algorithms.…”
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Neural network and Markov based combination prediction algorithm of video popularity by Xuesen MA, Shuyou CHEN, Xiangdong XU, Zhaokun CHU

“…Caching popular video into user-side in advance improves the user experience and reduces operator costs, which is a common practice in the industry.How to effectively predict the popularity of videos has become a hot issue in the industry.On account of the shortcomings of traditional prediction algorithms such as poor nonlinear mapping ability, low prediction accuracy and weak adaptability, a video popularity prediction algorithm based on a neural network and Markov combined model (Mar-BiLSTM) was proposed.Information dependencies were preserved by constructing bidirectional memory network model (bi-directional long short-term memory, BiLSTM), the prediction accuracy of the model was further improved by using Markov properties while avoiding the increase of the complexity of the model caused by the introduction of external variables.Experimental results show that compared with traditional time series and classic neural network algorithms, the proposed algorithm improves predicting accuracy, effectiveness and reduces the amount of calculation.…”
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