Deep learning has become popular in all aspect related to human judgments. Most machine learning techniques work well which includes text classification, text sequence learning, sentiment analysis, question-answer engine, etc. This paper has been focused on two objectives, firstly is to study...

In recent years, there has been a growing interest in Time Series forecasting. A number of time series forecasting methods have been proposed by various researchers. However, a common trend found in these methods is that they all underperform on a data set that exhibit uneven ups and downs...

Several initial center selection algorithms are proposed in the literature for numerical data, but the values of the categorical data are unordered so, these methods are not applicable to a categorical data set. This article investigates the initial center selection process for the categorical...

Load balancing applications introduce delays due to load relocation among various web servers and depend upon the design of balancing algorithms and resources required to share in the large and wide applications. The performance of web servers depends upon the efficient sharing of the resources...

The traffic increasing in the network creates bulk congestion while the bulk transfer of data evolves. Performance evaluation and high availability of servers are important factors to resolve this problem using various cluster based systems. There are several low-cost servers using the load...

The agricultural production is a process, which being nonlinear in nature, due to various influential parameters like weather, rainfall, diseases, disaster, area of cultivation etc., is not governed by any deterministic process. Fuzzy time series forecasting is one of the approaches for...