This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.

   This study includes Estimating scale parameter, location parameter  and reliability function  for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).

 Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (R_P=1000)

A simple and rapid spectrophotometric method for the determination of sulphite SO3-2 is described. The method is based on the rapid reduction of known amount of chromate CrO4-2 in the presence of sulphite in acidic medium of 2N H2SO4. The amount of excess of chromate was measured after it reactions with 1,5-diphenylcarbazide which finally gives a pink-violet, water soluble and stable complex, which exhibit a maximum absorption at 542 nm. Beer's law was obeyed in the concentration range from 0.004-6.0 µg of sulphite in a final volume of 25 ml with a molar absorbtivity of 4.64×104 l.mol-1.cm-1, Sandal's sensitivity index of 0.001724 ?g .cm-2 and relative standard deviation of ±0.55 - ±0.83 depending on the concentration level. The present

The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search the comparison between binary lo