Abstract Machine learning algorithms have been used widely in various applications and
areas. To fit a machine learning model into different problems, its hyper-parameters must be …

Abstract Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL)
research for their architectural advantages. CNN relies heavily on hyperparameter …

In many optimization problems arising from scientific, engineering and artificial intelligence
applications, objective and constraint functions are available only as the output of a black …

Plant diseases are considered one of the main factors influencing food production and
minimize losses in production, and it is essential that crop diseases have fast detection and …

This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …

Nowadays, hybrid soft computing technics are attracting the scholars of construction
materials field due to their high adaptability and prediction performances to data information …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

Dry gas pipelines can encounter various operational, technical, and environmental issues,
such as corrosion, leaks, spills, restrictions, and cyber threats. To address these difficulties …

Prediction of work Travel mode choice is one of the most important parts of travel demand
forecasting. Planners can achieve sustainability goals by accurately forecasting how people …

Algorithms for machine learning have found extensive use in numerous fields and
applications. One important aspect of effectively utilizing these algorithms is tuning the …