Building Student’s Study Path using Markov Chain Process with Apriori Cross Join Pearson Correlation

analysis of ruin probability for insurance companies using markov chain

در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...

Customer Relationship Management for Product Development Process using Pearson Correlation Coefficient with Data Mining Techniques

The Pearson correlation coefficient based on the customer relationship clearly illustrate to the product development process. It developed in an association from the customer relationship management process. The CRM should be implemented to the Pearson correlation algorithm. In an existing system is used to implement for a customer association management in an organization process implement for...

Fastest Mixing Markov Chain on a Path

Simulation using Markov chain Monte Carlo is a mainstay of scientific computing; see, e.g., [4, 5] for pointers to the literature. Thus the analysis and design of fast mixing Markov chains, with given stationary distribution, has become a research area. In [2], we show how to numerically find the fastest mixing Markov chain (i.e., the one with smallest secondlargest eigenvalue modulus) on a giv...

Pearson Product-Moment Correlation

Fast Optical Flow Using Cross Correlation and Shortest-Path Techniques

Optical flow or image motion estimation is important in the area of computer vision. This paper presents a fast and reliable optical flow algorithm which produces a dense optical flow map by using fast cross-correlation and shortest-path techniques. Fast correlation is achieved by using the box filtering technique which is invariant to the size of the correlation window. The motion for each sca...