تحتل التنمية الزراعية في معظم بلدان العالم مكانة مهمة ومتميزة لما لها من دور مهم في الحياة الاقتصادية والاجتماعية .ففي البلدان المتقدمة كان هناك دعم كبير  مالي وفني وعلمي وتكنولوجي من قبل الحكومات الى القطاع الزراعي على الرغم من الامكانيات المالية والفنية والادارية والتكنولوجية التي يمتلكها القطاع الخاص الزراعي.لذا فمن الضروري قيام الحكومات في البلدان الناميه بشكل عام والعراق بشكل خاص بتقديم كل اشكال

In this research weights, which are used, are estimated using General Least Square Estimation to estimate simple linear regression parameters when the depended variable, which is used, consists of two classes attributes variable (for Heteroscedastic problem) depending on Sequential Bayesian Approach instead of the Classical approach used before, Bayes approach provides the mechanism of tackling observations one by one in a sequential way, i .e each new observation will add a new piece of information for estimating the parameter of probability estimation of certain phenomenon of Bernoulli trials who research the depended variable in simple regression  linear equation. in addition to the information deduced from the past exper

Sliding Mode Controller (SMC) is a simple method and powerful technique to design a robust controller for nonlinear systems. It is an effective tool with acceptable performance. The major drawback is a classical Sliding Mode controller suffers from the chattering phenomenon which causes undesirable zigzag motion along the sliding surface. To overcome the snag of this classical approach, many methods were proposed and implemented. In this work, a Fuzzy controller was added to classical Sliding Mode controller in order to reduce the impact chattering problem. The new structure is called Sliding Mode Fuzzy controller (SMFC) which will also improve the properties and performance of the classical Sliding Mode control

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.

An aircraft's landing stage involves inherent hazards and problems associated with many factors, such as weather, runway conditions, pilot experiences, etc. The pilot is responsible for selecting the proper landing procedure based on information provided by the landing console operator (LCO). Given the likelihood of human decisions due to errors and biases, creating an intelligent system becomes important to predict accurate decisions. This paper proposes the fuzzy logic method, which intends to handle the uncertainty and ambiguity inherent in the landing phase, providing intelligent decision support to the pilot while reducing the workload of the LCO. The fuzzy system, built using the Mamdani approach in MATLAB software, considers critical