Environmental Evaluation via Waste Reduction Algorithm (WAR) of an Energy-Integrated Suspension PVC Production Process by Juan Manuel Diaz Perez, Antonio Mendivil-Arrieta, Angel D. Gonzalez-Delgado

“…An environmental assessment was carried out using the Waste Reduction Algorithm for a PVC production process with energy integration. …”
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A Noise Reduction Algorithm for White Noise and Periodic Narrowband Interference Noise in Partial Discharge Signals by Jiyuan Cao, Yanwen Wang, Weixiong Zhu, Yihe Zhang

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Energy consumption reduction method for green buildings based on human thermal discomfort posture recognition algorithm by Shijiu Song, Li Zhou

“…This research algorithm can timely and effectively identify the uncomfortable posture of the human body, thereby automatically adjusting indoor temperature and achieving energy conservation and emission reduction.…”
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Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors. by Prajakta Desai, Seng W Loke, Seng W Loke, Aniruddha Desai

“…This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. …”
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Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction by Ming-Wei Chang, Wen-tau Yih

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Predicting agricultural drought in central Europe by using machine learning algorithms by Endre Harsányi

“…The findings of this research promote RF as a reliable algorithm for predicting SPEI droughts.…”
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Prediction of growth and feed efficiency in mink using machine learning algorithms by A. Shirzadifar, G. Manafiazar, P. Davoudi, D. Do, G. Hu, Y. Miar

“…The XGB algorithm can be an accurate algorithm to predict the ADG, FCR, and RFI values without measuring costly daily feed intake. …”
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Hybrid machine learning algorithms accurately predict marine ecological communities by Luciana Erika Yaginuma, Luciana Erika Yaginuma, Fabiane Gallucci, Danilo Cândido Vieira, Paula Foltran Gheller, Simone Brito de Jesus, Thais Navajas Corbisier, Gustavo Fonseca

“…Predicting ecological communities is highly challenging but necessary to establish effective conservation and monitoring programs. …”
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Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms by Cihan Çakmakçı

“…There were no differences between the means of actual and predicted LWs by machine learning models. The fact that the models generalized well on the testing data sets indicates that machine learning algorithms have valid predictive patterns and are effective methods in LW weight of Norduz sheep. …”
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Multiple Machine Learning Algorithms-based NBA Team Playoffs Prediction by Yeung Manho

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Appropriate Combination of Artificial Intelligence and Algorithms for Increasing Predictive Accuracy Management by Shahram Gilani Nia

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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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Phase diagram construction and prediction method based on machine learning algorithms by Shengkun Xi, Jiahui Li, Longke Bao, Rongpei Shi, Haijun Zhang, Xiaoyu Chong, Zhou Li, Cuiping Wang, Xingjun Liu

“…Meanwhile, the CALPHAD method has accumulated abundant high-quality phase diagram data who would be the perfect training data for the machine learning algorithms. In the present work, a phase diagram prediction method which integrates machine learning algorithms with CALPHAD descriptors is proposed. …”
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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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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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