Artificial Neural Networks and Advanced Fuzzy Techniques for Predicting Noise Level in the Industrial Embroidery Workrooms

Mohsen AliabadiDepartment of Occupational Hygiene, Faculty of Public Health, Hamadan University of Medical Sciences, Hamadan, IranCorrespondence[email protected] [email protected]

Rostam GolmohammadiDepartment of Occupational Hygiene, Faculty of Public Health and Center for Health Researches, Hamadan University of Medical Sciences, Hamadan, Iran

Hassan KhotanlouDepartment of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan, Iran

Muharram MansoorizadehDepartment of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan, Iran

Amir SalarpourDepartment of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan, Iran

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Mirwan Ushada, Tsuyoshi Okayama, Nafis Khuriyati & Atris Suyantohadi. (2017) Affective Temperature Control in Food SMEs using Artificial Neural Network. Applied Artificial Intelligence 31:7-8, pages 555-567.
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Antônio José Vinha Zanuncio, Amélia Guimarães Carvalho, Carlos Alberto Araújo Júnior, Maíra Reis de Assis & Liniker Fernandes da Silva. (2019) Neuro-fuzzy Hybrid System for Monitoring Wood Moisture Content During Drying. Floresta e Ambiente 26:2.
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N. S. Rosli, R. Ibrahim & I. Ismail. (2016) Neural network model with particle swarm optimization for prediction in gas metering systems. Neural network model with particle swarm optimization for prediction in gas metering systems.

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Artificial Neural Networks and Advanced Fuzzy Techniques for Predicting Noise Level in the Industrial Embroidery Workrooms

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Artificial Neural Networks and Advanced Fuzzy Techniques for Predicting Noise Level in the Industrial Embroidery Workrooms

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