This paper investigates the local linear model tree (LOLIMOT), a typical neural fuzzy model, in multiple-input-multiple-output predictive control (MPC). In conventional LOLIMOT, structural parameters including centres and variances of its Gaussian kernels are set based on equally dividing input data space. this paper, after initially obtained from space partition, they optimized by gradient des...

Abstract A novel predictive modeling framework for the spread of infectious diseases using high-dimensional partial differential equations is developed and implemented. scalar function representing infected population defined on a space its evolution over all directions described by balance equation (PBE). New infections are introduced among susceptible from non-quarantined based their interact...

A number of new predictive modeling techniques have emerged in the past several years. These methods can be used independently or in combination with traditional modeling techniques to produce useful tools for the management of prostate cancer. Investigators should be aware of these techniques and avail themselves of their potentially useful properties. This review outlines selected predictive ...

This paper demonstrates the use of Data Mining (DM) techniques in exploratory research. A robust model for identifying the factors that explain the success of Open Source Software (OSS) projects is created, validated and tested. The predictive modeling techniques of Logistic Regression (LR), Decision Trees (DT) and Neural Networks (NN) are used together in this analysis. Using Text Mining resul...

The wallet of a customer is defined as the total amount this customer can spend in a specific product category. This is a vital piece of information for planning marketing and sales efforts. We discuss the important problem of customer wallet estimation, while emphasizing the use of predictive modeling technologies to generate useful estimates, and minimizing reliance on primary research. We su...

The proliferation of data collection technologies often results in large sets with many observations and variables. In practice, highly relevant engineered features are groups predictors that share a common regression coefficient (i.e., the group affect response only via their collective sum), where unknown advance must be discovered from data. We propose an algorithm called tree (CTR) to disco...