Azme Khamis

Fuzzy Entire Sequence Spaces

We first investigate the notion of fuzzy entire sequence space with a suitable example. Also we deal with the properties of the space of fuzzy entire sequences. The concepts of subset and superset of the fuzzy entire sequence spaces are introduced and their properties are discussed.

FUZZIFICATION OF QUANTITATIVE DATA TO PREDICT TUMOUR SIZE OF COLORECTAL CANCER

Regression analysis has become more popular among researchers as a standard tool in analyzing data. This paper used fuzzy linear regression model (FLRM) to predict tumour size of colorectal cancer (CRC) data in Malaysia. 180 patients with colorectal cancer received treatment in hospital were recorded by nurses and doctors. Based on the patient records, a triangular fuzzy data will be built toward the size of the tumour. Mean square error (MSE) and root mean square error (RMSE) will be measured as a part of the process for predicting the size of the tumour. The degree of fitting adjusted is set between 0 and 1 in order to find the least error. It was found that the combination of FLRM model with fuzzy data provided a better prediction compared to the FLRM model alone. Hence, this study concluded that the tumour size is directly proportional to several factors such as gender, ethnic, icd 10, TNM staging, diabetes mellitus, Crohn’s disease, ulcerative colitis, polyp, history of cancer, endometrial, small bowel, hepatobiliary, urinary tract, ovarian, other cancer, colorectal, weight loss, diarrhea, blood stool and abdominal.

Descriptive statistics with Box-Jenkins and marketing research for jewellery company in Malaysia

We develop and demonstrate a methodology for Chinese Jewellery companies for raising their sales and promoting the quality of their products and services. A questionnaire form is used for company’s sale report, and also to identify the customer satisfaction towards the shop. The data that we got from questionnaire form was analyzed using descriptive statistics. The forecast value for daily market price of gold deviates from the actual value due to unpredictable factors such as politic and economy issues, the 916 gold has higher sales at the peak season like festival during which there is some weakness in their products and services.

A COMPARATIVE STUDY FOR SOLVING NON-CLASSICAL OPTIMAL CONTROL PROBLEM USING EULER, RUNGE-KUTTA AND SHOOTING METHODS

A current optimal control problem has the numerical properties that do not fall into the standard optimal control problem detailing. In our concern, the state incentive at the final time, y(T ) = z, is free and obscure, and furthermore, the integrand is a piecewise consistent capacity of the obscure esteem y(T ). This is not a standard optimal control problem and cannot be settled utilizing Pontryagin’s minimum principle with the standard limit conditions at the final time. In the standard issue, a free final state y(T ) yields an important limit condition p(T ) = 0, where p(t) is the costate. Since the integrand is a component of y(T ), the new fundamental condition is that y(T ) yields to be equivalent to a necessary consistent capacity of z. We tackle a case utilizing a C++ shooting method with Newton emphasis for tackling the two point boundary value problem (TPBVP). The limiting free y(T ) value is computed in an external circle emphasis through the golden section method. Comparative nonlinear programming through Euler and Runge-Kutta is also presented.

Intuitionistic N-fuzzy set and its application in biΓ-ternary semigroups

This paper aims at introducing the notion of intuitionistic N-fuzzy set (INFS) and its application along with its examples. As the application of this set, its idea has been applied to a newly defined algebraic structure “BiΓ-Ternary Semigroup”. The notions of intuitionistic N-fuzzy biΓ-ternary subsemigroup and intuitionistic N-fuzzy biΓ-left (right, lateral and bi) ideals have been defined and related properties have been investigated here. The characterization of biΓ-ternary semigroup under these ideals has been established.

Forecasting sunspot numbers with Feedforward Neural Networks (FNN) using ‘Sunspot Neural Forecaster’ system

This paper presents the investigations of forecasting performance of different type of Feedforward Neural Networks (FNN) in forecasting the sunspot numbers. Feedforward Neural Network will be used in this investigation by using different learning algorithms, sunspot data models and FNN transfer functions. Simulations are done using Matlab 7 where customized Graphic User Interface (GUI) called ‘Sunspot Neural Forecaster’ have been developed for analysis. A complete analysis for different learning algorithms, sunspot data models and FNN transfer functions are examined in terms of Mean Square Error (MSE) and correlation analysis. Finally, the best optimized FNN parameters will be used to forecast the sunspot numbers.

t-Best approximation in intuitionistic fuzzy normed spaces

We study the problems of t-best approximation in intuitionistic fuzzy normed spaces. The set of all t-best approximation define the t-proximinal set, F-best approximation and prove some theorems on these sets.