Document Details

Document Type : Thesis 
Document Title :
A METHODOLOGY FOR DRASTIC IMPROVEMENT OF GOODNESS OF FIT APPLIED TO ACTUAL EMPIRICAL DATA BY USING ARTIFICIAL INTELLIGENCE (AI)
منهجية لتحسين جذري في دقة مطابقة البيانات الواقعية لبيانات المحاكاة مع تطبيق حيوي باستخدام الذكاء الصناعي
 
Subject : Faculty of Engineering 
Document Language : Arabic 
Abstract : Scientists and practitioners frequently resort to replicating empirical data when testing the validity of scientific theories or testing hypothesis. Commonly known probability distribution (Normal, Binomial, Exponential, etc.) are habitually assumed to fit the empirical data. In order to avoid complicated probability distributions, analysts find themselves tolerating poor values for goodness of fit. In this thesis, we have introduced a methodology that replicates a distribution much closer to the actual distribution of the data. The superiority of the proposed methodology over use known probability distribution (Normal, Binomial, Exponential, etc.), by how small the absolute percentage of error (in many cases, the absolute percentage is practically equal to zero %). Meaning that replicated data is exactly identical to the actual data. The use of Artificial intelligence (AI) has facilitated automatic generation of precise mathematical formulas needed. Practicality of proposed method is shown by assisting Military Training Institute (MTI) in producing very effective future training plans. Whereas, the proposed solution method was used to obtain a distribution of data exactly identical to the distribution of the original data. The results were impressive, with 100% goodness of fit. 
Supervisor : Prof. Ahmad A. Moreb 
Thesis Type : Master Thesis 
Publishing Year : 1442 AH
2020 AD 
Added Date : Monday, August 31, 2020 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
نايف ناحي الحربيAlharbi, Naif NahiResearcherMaster 

Files

File NameTypeDescription
 46711.pdf pdf 

Back To Researches Page