Since the launch of the first land observation satellite Landsat-1 in 1972, many machine learning algorithms have been used to classify pixels in Thematic Mapper (TM) imagery. Classification methods range from parametric supervised classification algorithms such as maximum likelihood, unsupervised algorithms such as ISODAT and k-means clustering to machine learning algorithms such as artificial...

The ability to read and write Javanese scripts is one of the most important competencies for students have in order preserve language as Indonesian cultures. In this study, we developed a predictive model 20 characters using random forest algorithm basis developing script learning media students. building model, used an extensive handwritten image dataset experimented with several different pre...

Global solar radiation estimation is crucial for regional climate assessment and crop growth. Therefore, studies on the prediction of are emerging. With availability public data radiation, computerized models have been developed as well. These predictive play significant role in determining potentials regions suitable renewable energy generation required by engineering agricultural activities. ...

<p><span lang="EN-US">Today, the world lives in era of information and data. Therefore, it has become vital to collect keep them a database perform set processes obtain essential details. The null value problem will appear through these processes, which significantly influences behaviour such as analysis prediction gives inaccurate outcomes. In this concern, authors decide utilise r...

Since the first application of Artificial Intelligence in field hydrology, there has been a great deal interest exploring aspects future enhancements to hydrology. This is evidenced by increasing number relevant publications published. Random forests (RF) are supervised machine learning algorithms that have lately gained popularity water resource applications. It used variety research domains, ...