الذكاء هو القدرة على فهم و تعلم الأشياء.
الذكاء الطبيعي هو كائن له دماغ, او شيء ما, يمكنه من التعلم, و الفهم, و حل المشكلات و اتخاذ القرارات.
الذكاء الصنعي علم يبحث في السلوك الذكي لغير الكائنات الحية.
This research work presents fuzzy pitch controller design of wind turbine to get the maximum power in
addition to decrease the losses caused by acceleration and deceleration in turbine rotation. And thus
optimize power coefficient of turbine throug
h artificial intelligence and in particular fuzzy logic, because
the fuzzy controller doesn’t need a complex mathematical pattern of the controlled system.
A fuzzy controller is designed and compared with conventional controller for the same purpose in a wind
turbine system described by its transfer function and membership function has been chosen for error and
accumulation errors signals by using MATLAB. Results have been compared and showed better response
by using the fuzzy controller.
In this research, we try to show the major features of prolog which make it
a strong expressive language about writing the expert systems and the
traditional languages lacks them as Pascal language. We also provide expert
system, the purpose of it
is the Inventory Control by apply the Fixed-Order
Quantity Model, and we clearified concept of the static and dynamic data in
Prolog. Finally, we compared between the databases in prolog and some of
their quires with Access and SQL.
Expert systems are considered as one of the main applications of artificial
intelligence, which are known as knowledge based systems. And the expert
systems are computer applications which embody some non-algorithmic
expertise for solving certain types of problems. For example, the problems
which provide advice, analysis, classification, diagnostic, explanation, teaching,
or designing…etc.
This study has been done to develop scientific research and select talented people of
post-graduate students (master students) to continue and get doctoral degrees (degree in
PHD) at Tishreen University. The research has been prepared, which aims t
o suggest a
model for measuring the degree of creativity and talent for post-graduate students by using
one of artificial intelligence techniques such as Fuzzy Logic.
An expert system has been built that contains an inference rule which consists of
three types of tests: (Theory Test, TT), (Practice Test, PT), and (Creativity Test, CT) for
each course.
This intelligent system has also aimed to determine the ability to make decisions
which gives the rate of talent for post- graduate students.
The study has reached to an important set of results, and the most important is:
Results have shown high strength and reliability shows the validity of this proposed
model, the validity of the results have reached to 85% and 100%, by using two different
methods to defuzzificate of proposed model.
The main goal of data mining process is to extract information and
discover knowledge from huge databases, where the clustering is
one of the most important functionalities which can be done in this
area. There are many of clustering algorithms an
d methods, but
determining or estimating the number of clusters which should be
extracted from a dataset is one of the most important issues most of
these methods encounter it. This research focuses on the problem of
estimating number of clusters in the case of agglomerative
hierarchical clustering. We present an evaluation of three of the
most common methods used in estimating number of clusters.
The Research Aims:
Syrian organizations keep large amounts of information and data about their
personnel in their IT systems. This information, however, is often left unutilized or
may be analyzed through statistical methods. In this study, DM is
considered a
solution for analyzing HR data and explore knowledge from data stored in some
Syrian organization through two major stages:
Stage A: Using results of Semi-Annual performance evaluation process to build
prototype showed in (Fig. 6) to accomplish two tasks:
1. Building a models to predict appropriate job function for an employee
through majority principle and using high accuracy result to increase the
number of training data and make it self-learning model.
2. Choose most important attributes that used in classify methods to use it in
personnel selection and recruitment.
Stage B: Using data of Time & Attendance to analysis personnel activity through
clustering methods and building many meaningful groups.