Keywords : fuzzy logic


Information Retrieval System for Digital Libraries Using Fuzzy Logic

Ghaydaa A.A. Al-Talib; Nawar Abdul Ghani

AL-Rafidain Journal of Computer Sciences and Mathematics, 2010, Volume 7, Issue 3, Pages 243-258
DOI: 10.33899/csmj.2010.163941

This research is one of the important steps towards processing the most significant challenge in digital libraries and web, which is computing document’s rank, its importance, and its relevance to the user information need. This is achieved through the utilization of fuzzy logic high potential capabilities in dealing with such sort of problems and providing notable flexibility for the user to get his favorite subjects.
The research is concerned with designing and implementing a proposed information retrieval system, called FIRS (Fuzzy Information Retrieval System). This system is developed to deal with huge database, which contains different text file types and sizes. This database is distributed over a collection of server computers, connected with the intranet network that is dedicated for this system.
The system has the ability for mining of data available in this database and retrieving the useful information that corresponds with the user need. This is accomplished through applying the proposed algorithms for indexing process, document’s rank computations, generating keywords process, and finally, displaying information retrieval results. The proposed system gives high quality results comparing with other information retrieving algorithms.
 

Genetic Pattern Recognition using Intelligent Techniques

Basil Younis Thanoon; Omar Saber Qasim

AL-Rafidain Journal of Computer Sciences and Mathematics, 2010, Volume 7, Issue 3, Pages 161-172
DOI: 10.33899/csmj.2010.163935

In this research a light is shed on converting DNA series to amino acid being responsible for forming protein through intelligent techniques. Some comparisons have been made between particularly Artificial Neural Network, Fuzzy Logic and Genetic Algorithms for discovering the powerful and the week ones in particle way. The hybrid operation has been made between Artificial Neural Network and Fuzzy Logic t to get a hybrid technique in a new formula having robust results than the original ones.
 
 

Design a Fuzzy Expert System for Liver and Pancreas Diseases Diagnosis

Baydaa S Bhnam

AL-Rafidain Journal of Computer Sciences and Mathematics, 2010, Volume 7, Issue 2, Pages 129-141
DOI: 10.33899/csmj.2010.163891

Fuzzy logic is a branch of artificial intelligence techniques, it deals with uncertainty in knowledge that simulates human reasoning in incomplete or fuzzy data. Fuzzy relational inference that has applied in medical diagnosis was used within the medical knowledge base system to deals with diagnostic activity, treatment recommendation and patient's administration.
            In this research, a medical fuzzy expert system named (Liv&PanFES) has been developed for diagnosis and decision making of general Liver and Pancreas diseases.
       The (Liv&PanFES) is a rule based fuzzy expert system, results of laboratory analysis are inserted into the system. This system can define the probable diagnosis on these data, and later on it can pick out the most probable one for disease.
 

Processing of Scheduling Problems in the Job Shop Using Fuzzy Logic

Baydaa S Bhnam

AL-Rafidain Journal of Computer Sciences and Mathematics, 2010, Volume 7, Issue 1, Pages 45-65
DOI: 10.33899/csmj.2010.163863

The research deals with a problem that concentrates on the use of fuzzy logic which sends the job orders for the purpose of the due dates to achieve  customer's satisfaction besides efficient flow of jobs among the production cells. To achieve the aims of the research , an algorithm for scheduling jobs has been achieved in the job shop which treats N jobs ( J1, J2,…..Jn) on M  machines (M1, M2,….Mm) . This algorithm is based on triangular member ship functions to express the fuzzy processing times and that through the treatment time of the operation and the release date and the due date.
The most notable findings of the research is the high degree of satisfaction of the job that are at the forefront  of chain, while it begins to decline whenever the sequence increases, i.e is whenever the number of the acts increases in the waiting line, and that is by determining the start time and end time of each job.
 

Evaluation of Electrons Energy Distribution Function by Fuzzy Logic

Nabhan A. Hamdon

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 3, Pages 127-144
DOI: 10.33899/csmj.2009.163841

Evaluation of a maxwellian Electrons Energy Distribution Function (EEDF) in plasma glow discharge in air has been done. It includes the design of computerized system which depends on one of the intelligent techniques (Fuzzy logic). Their input and output consists of linguistic variables which describe the fundamental parameters (Energy, Pressure, Discharge current) of glow discharge process in different glow discharge regions (Cathode fall region, positive column region). It is suggested in this study that three different types of Gaussian membership function in different forms for each variable. The results seem to be compatible with other published researches, making use of the MATLAB scientific software version (R2006a).
 

Remove Noise from Grayscale Digital Images by Traditional and Fuzzy Filters

Baydaa I. Khalil

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 2, Pages 47-100
DOI: 10.33899/csmj.2009.163815

Image denoising and enhancement is an important field and it is used very much in image processing, where images are corrupted by many kinds of noise, therefore, methods and techniques must be used to remove these noises. In this research seven traditional filters are used to remove noise from digital images corrupted with salt&pepper noise and Gaussian noise. And also adopting principle of fuzzy logic to hybrid between traditional filters and fuzzy logic using double bell shaped membership function and also hybrid with double adjusted sigmoid  membership function to create seven fuzzy sigmoidal filters. After applying seven traditional methods, seven fuzzy bell methods and seven fuzzy sigmoidal methods , by using measures of restored image PSNR, MSE, MAE , shows the final methods i.e. seven fuzzy sigmoidal methods are better than other filters i.e. methods that are used in this research after comparing the results.
 

Artificial Intelligent Techniques with Watermarking

Nada N. Saleem; Baydaa I. Khaleel; Shahbaa I. Khaleel

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 2, Pages 229-266
DOI: 10.33899/csmj.2009.163810

This research presents three robust blind watermarking algorithms in the discrete wavelet transform and spatial domain based on neural network and fuzzy logic artificial intelligent techniques. To enhance the performance of the watermarking system the first algorithm is developed by combining Radial Basis Function (RBF) neural network with Discrete Wavelet Transform (DWT) using (DWT-RBFW) algorithm for embedding and extracting of watermark. The second developed (RBFW) algorithm used RBF neural network for embedding and extracting of watermark based on intensity of whole image. The third developed (FL-EXPW) watermarking method is based on fuzzy logic and expert system techniques and it’s the best algorithm among the three methods. The developed watermarking algorithms are robust against various attacks signal processing operations such as additive noise and jpeg compression, and geometric transformations.
 

Design a Fuzzy Expert System for Pediatrics Diseases Diagnosis

Nada N. Saleem

AL-Rafidain Journal of Computer Sciences and Mathematics, 2008, Volume 5, Issue 2, Pages 155-172
DOI: 10.33899/csmj.2008.163979

Fuzzy logic is a branch of artificial intelligence techniques, it deals with uncertainty in knowledge that simulates human reasoning in incomplete or fuzzy data. Fuzzy relational inference that was applied in medical diagnosis was used within the medical knowledge base system to deal with diagnostic activity, treatment recommendation and patient's administration.
In this research, a medical fuzzy expert system named (PedFES) has been developed for diagnosis and decision making of general pediatrics diseases.
The (PedFES) is a rule based fuzzy expert system, the results of laboratory analysis are inserted into the system. This system can define the probable diagnosis depending on these data, and later on it can pick out the most probable one for disease.
 

Using Fuzzy Logic to Construction of Expert Computer Model for Forecast of Compressive Strength of the Portland Cement

Basil Y. Al-Khayyat; Sufyan S. Al-Dabbagh

AL-Rafidain Journal of Computer Sciences and Mathematics, 2005, Volume 2, Issue 2, Pages 29-49
DOI: 10.33899/csmj.2005.164087

The present study aims at construction of expert computer model for forecast of compressive strength of the Portland cement. This model is achieved by chemical data input through interface designed by matlab program. This is followed by calculation of the content of phases; namely, C3S , C2S , C3A and C4AF. Later on , connection with fuzzy logic interface were made. The formentioned phases represent the input to the fuzzy logic interface through the condition rules IF-THEN. After defuzzification, the values of cement compressive strength appeared on the interface. The evaluations were made through calculation of square difference of the results of fuzzy logic ( present study) and statistical methods.