Decision making is a difficult task over the complex, spirited and competitive environment. A variety of research provides diverse notification for individual failure in making logical decisions under certain circumstances by applying normative approaches. In today's competitive market, the advance of technology is closely related to consumer needs for the extraction of good quality products at less cost which is in rarely finding a model in Consumer to Business (C2B). The aim of the paper is to optimize the C2B model by intuitionistic Fuzzy to resolve multi decision making problems. It derives multi criteria decision making to support complex environments in C2B using membership and non-membership attributes which is built to generate the intuitionistic fuzzy priority weighting vector based on minimum distance and similarity measures. This technique classifies the object type as per the customer needs with a ranking in the optimized way make efficient for the customer satisfaction. © 2017 IEEE.

Chandra Segar T

Department of Digital Communications

School of Information Technology and Engineering

Vellore Campus

Senthilkumar M

Department of Software and Systems Engineering

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

An assessment framework of intuitionistic fuzzy network for C2B decision making

2017 4th International Conference on Electronics and Communication Systems (ICECS)

Stock price forecasting is a prevalent and critical subject in financial and academic studies. The objective of this paper is to forecast today's high price in the market from open of today, open from yesterday and closing of yesterday. We are using the real dataset from NSE NIFTY. We will be implementing a fuzzy intuition system such as Mamdani, Sugeno, and machine learning algorithms like CNN and LSTM. Cost optimization would be used for Sugeno. This paper would compare and improvise the algorithm which will show a higher prediction accuracy rate and would be proved statistically. © 2019 IEEE.

2019 Innovations in Power and Advanced Computing Technologies (i-PACT)

Prediction of Share Market using FIS

This paper mainly focuses on the design aspects of force balance measurement system for aerodynamic vehicle flying at hypersonic speed. When the speed of vehicle is hypersonic, additional aerodynamic heating creates difficulty in the system and needs change in the design geometry and material type .For the purpose of examining the model we have considered a simulation of blunt cone with following parameters like, length of the string, diameter of string, material of string, drag coefficient, pressure, velocity, density of air, Mach number, Reynolds’s number, stagnation enthalpy were suitably selected. CFD is used as a tool to calculate the drag force generated under the hypersonic conditions. A measurement system was developed for measuring the strain developed in the blunt cone when it is subjected to shock force. The measurement system was calibrated statically using hang weight and dynamically using impact load test performed on the string, from the calibration test impulse response function is calculated. And a fuzzy predication based approach was developed to predict the strain developed in the system.

Materials Today: Proceedings

One-Dimension Force Balance System for Hypersonic Vehicle an experimental and Fuzzy Prediction Approach

This paper is carried on the heuristic prediction of rainfall using machine learning techniques. As we know agriculture was the predominant of our country and economy. While a regular rain pattern is usually played vital for healthy agriculture but too much rainfall or too little rainfall can be harmful, even it led to devastating of crops. This paper discusses the rate of rainfall in previous years according to various crops seasons like rabi, Kharif, zaid and predicts the rainfall in future seasons. The paper also measures the different categories of data by linear regression method in metrics for effective understanding of agriculture in India. We have selected a real dataset which consists of past year's rainfall rate according to various seasons. Results of this application help farmers to make a correct decision to harvest a particular crop accordingly to crops seasons. Linear regression helps to find. © 2017 IEEE.

2017 International Conference on Trends in Electronics and Informatics (ICEI)

Heuristic prediction of rainfall using machine learning techniques

In statistical analysis, we have a collection of data, with the use of these data, we have to do analysis based on our requirements. With the collection of data using Statistical analysis, we deal collection, analysis, presentation and organizing the data. With the help of statistical analysis, we can find underlying patterns, relationships, and trends between data samples. The R system for statistical computing is an environment for data analysis and graphics. Here we are going to implement boxplot method and control chart methods for sales analysis in a stationary shop dataset. With the help of boxplot, we can easily make relations between samples and we can find the outliers. © 2017 IEEE.

Journal	Data powered by Typeset2017 4th International Conference on Electronics and Communication Systems (ICECS)
Publisher	Data powered by TypesetIEEE
Open Access	0