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Prediction of Total Soluble Solids and pH of Strawberry Fruits Using RGB, HSV and HSL Colour Spaces and Machine Learning Models

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Machine Learning-Based Microclimate Model for Indoor Air Temperature and Relative Humidity Prediction in a Swine Building

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Systematic review of animal-based indicators to measure thermal, social, and immune-related stress in pigs

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From Reality to Virtuality: Revolutionizing Livestock Farming Through Digital Twins

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Non-Destructive Estimation of Fruit Weight of Strawberry Using Machine Learning Models

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Modelling methane emissions from pig manure using statistical and machine learning methods

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Prediction of Strawberry Leaf Color Using RGB Mean Values Based on Soil Physicochemical Parameters Using Machine Learning Models

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Impact of Climate Change and Heat Stress on Milk Production in Korean Holstein Cows: A Large-Scale Data Analysis

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Applicability of statistical and machine learning–based regression algorithms in modeling of carbon dioxide emission in experimental pig barns

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Prediction of body composition in growing-finishing pigs using ultrasound based back-fat depth approach and machine learning algorithms

Basak, J. K., Paudel, B., Deb, N. C., et al. (2023) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2023.108269 · Cited by 19 · see citing works

Predicting the growth performance of growing-finishing pigs based on net energy and digestible lysine intake using multiple regression and artificial neural networks models

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Development and Validation of Low-Cost Indoor Air Quality Monitoring System for Swine Buildings

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Prediction of drinking water requirements by applying statistical and machine learning models in growing-finishing stage of pigs

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Evaluation of crop water stress index of wheat by using machine learning models

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Modeling of process parameters to predict the efficiency of shallots stem cutting machine using multiple regression and artificial neural network

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Machine learning prediction of groundwater arsenic contamination using water quality parameters in the coastal region of Bangladesh

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Artificial Neural Network Models for the Prediction of Ammonia Concentrations in a Mediterranean Dairy Barn

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Prediction of digestible energy requirement in growing finishing stage of pigs using machine learning models

Deb, N. C., Basak, J. K., Karki, S., Arulmozhi, E., Kang, D. Y., Tamrakar, N., Seo, E. W., Kook, J., Kang, M. Y., & Kim, H. T. (2025) · Journal of Agriculture and Food Research · doi:10.1016/j.jafr.2025.101700 · Cited by 4 · see citing works

Evaluation of Body Surface Temperature in Pigs Using Geostatistics

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Optimized GMAW parameters for enhancing mechanical properties of dissimilar AA6061 and AA7075 alloy welds using hybrid ANN-GA approach

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Development of prediction model for body weight and energy balance indicators from milk traits in lactating dairy cows based on deep neural networks

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Application of machine learning models for zooplankton abundance prediction in ponds of Southeastern Coastal Regions in Bangladesh

Basak, J. K., Sonet, S. S., Rumman, R., et al. (2025) · Environmental Monitoring and Assessment · doi:10.1007/s10661-025-14382-y · Cited by 3 · see citing works

Machine Learning Models for Predicting Indoor Air Temperature of Smart Building

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A machine learning system to evaluate physiological parameters and heat stress for sows in gestation crates

Zhuang, Y., Cao, M., Ji, H., Liu, Y., Li, S., Zhang, J., Wang, C., & Teng, G. (2025) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2025.110828 · Cited by 2 · see citing works

Modeling aquatic insect populations and biodiversity indices in freshwater bodies using machine learning algorithms

Sonet, S. S., Basak, J. K., Akter, S., Paudel, B., Rumman, R., & Jhan, P. K. (2025) · Hydrobiologia · doi:10.1007/s10750-025-06067-x · Cited by 2 · see citing works

Modeling of BOD and COD Concentrations in Aquaculture Sites of the Southeastern Coastal Region of Bangladesh Using Machine Learning

Chakraborty, M., Ismail, M., Basak, J. K., et al. (2026) · Water Environment Research · doi:10.1002/wer.70480 · Cited by 1 · see citing works

The Influence of External Parameters on the Ripeness of Pumpkins

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Effect of operating variables on isopropanol absorbed by triethylene glycol solution and discussions on the mass transfer coefficient predicted by artificial neural network

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Prediction of Indoor Temperature in an Experimental Pig Barn by Using Machine Learning Model

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A System for Evaluating Physiological Parameters and Heat Stress in Sow House Based on Machine Learning and LabviewPreprint

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Prediction of Feed Intake during Growing Finishing Stage of Pigs Using Machine Learning Model

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Analisis Produktivitas dan Kualitas Buah Stoberi var Sujarli (Rosalinda) Berdasarkan Model Budidaya dan Pengolahan Citra Digital

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Explainable machine learning for skin temperature estimation in group-housed finishing pigs

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Systematic review on mechanistic thermal models of pigs: A comparative study

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Prediction of Soil Moisture Constants in Coastal Soils of Bangladesh Using Machine Learning Algorithms

Islam, M. S., Ismail, M., Basak, J. K., et al. (2026) · Irrigation and Drainage · doi:10.1002/ird.70185

Prediction of fecal coliform concentration in coastal surface water using machine learning algorithms and water quality parameters

Basak, J. K., Hasan, S., Ismail, M., et al. (2026) · Journal of Microbiological Methods · doi:10.1016/j.mimet.2026.107699

Weighted sigmoid gate unit for an activation function of deep neural network

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Evaluation of Sigmoid and ReLU Activation Functions Using Asymptotic Method

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Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural NetworkPreprint

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A Novel Activation Function in Convolutional Neural Network for Image Classification in Deep Learning

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The generalized sigmoid activation function: Competitive supervised learning

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