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Artificial intelligence techniques for the development of statistical Automatic learning

تقنيات الذكاء الاصطناعي لتطوير التعلم الآلي الاحصائي

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 Publication date 2020
and research's language is العربية
 Created by Shamra Editor




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The word "massive data" spread in 2017 and became the most common in the industry of advanced technology, it uses automated learning that allows computers to analyze past data and predict future data widely in familiar places. Non-automated learning professionals can use it too. To study the analytical method of statistical Automatic learning, it is necessary to identify the concept of artificial intelligence and its main classification and analytical techniques included and represent in automatic learning and deep learning. Automatic learning has developed thanks to some breakthroughs in artificial intelligence. It is an awareness of the efficient teaching of computers in addition to the invention of the Internet. Neural networks have an important role to play in teaching computers, such as humans, where they use data they can access to make decisions. There are many algorithms for learning about automatic learning. In our study, we demonstrate the methods and applications of automated statistical analysis, such as regression analysis, decision tree, middle method k and association analysis.

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المسؤولية الجنائية للذكاء الاصطناعي تتمثل أهمية هذه الدراسة في أهمية موضوعها الجديد والحيوي، وهو المسؤولية الجنائية الناتجة عن أخطاء الذكاء الاصطناعي في التشريع الإماراتي "دراسة مقارنة"، فعلى امتداد الخمسين سنة الماضية تضافرت الجهود العالمية في عدد من الميادين، كالفلسفة والقانون وعلم النفس وعلم المنطق والرياضيات، وعلم الأحياء وغيرها من العلوم، ومنذ سنوات بدأت هذه الجهود تحصد من ثمارها وظهرت إلى الوجود تطبيقات مذهلة للذكاء الاصطناعي، وهذا ما دفع دولة الإمارات العربية المتحدة لاستحداث وزارة للذكاء الاصطناعي وعلوم المستقبل، فهذه الخطوة تُضاف إلى سجل الإمارات الحافل بكل ما هو جديد في الثقافة والعلوم وغيرها من المجالات، فالإمارات سبّاقة في البحث وجلب أي أفكار جديدة أو عالمية وتطبيقها، والهدف من ذلك هو الارتقاء بالعمل الإداري. لأن اعتماد الإدارة على الذكاء الاصطناعي يساعدها على التكيف مع التغيرات المتلاحقة، ويساعدها أيضاً على مواجهة التحديات المتعددة والمختلفة، وبالتالي تحقيق الميزة التنافسية التي تسعى الإدارة إلى تحقيقها.
The entry of computer to many areas, such as medical field, led to develop new technique that has led to the prosperity of these areas, and helped doctors to detect and diagnose diseases accurately and credibility, where the experience of the docto r in addition to the accuracy of computer lead to access to the credibility of high patient and save human lives. A new approach for cardiac diseases detection and classification in ECG signals images is proposed using Adaptive Neuro Fuzzy Inference System ANFIS. The proposed approach is applied on database containing (147) ECG images, each of them accompanied with its medical report. The medical reports were used to validate the detection and classification. The proposed method achieved a relatively high accuracy (97%) in detection and classification processes. The proposed approach is developed using MATLAB, and based on its libraries, image processing, neural network and fuzzy logic.
Through our research we develop an Expert System called Transformer Fault Detection and abbreviation Exformer, to help engineers and technical's in detecting and diagnosis of oiled power transformer faults before it going out of service. We also u se Fuzzy Logic in ambiguous data cases about gas ratios in transformer oil, which require use of fuzzy rules in knowledge base of expert system. We also discuss basis of using Artificial Neural Networks and choose number of layers, number of neurons and suitable neural network for power transformers faults analysis and compare.
In this paper, it has merged two techniques of the artificial intelligent, they are the ants colony optimization algorithm and the genetic algorithm, to The recurrent reinforcement learning trading system optimization. The proposed trading system is based on an ant colony optimization algorithm and the genetic algorithm to select an optimal group of technical indicators, and fundamental indicators.
In recent years, time-critical processing or real-time processing and analytics of bid data have received a significant amount of attentions. There are many areas/domains where real-time processing of data and making timely decision can save thousand s of human lives, minimizing the risks of human lives and resources, enhance the quality of human lives, enhance the chance of profitability, efficient resources management etc. This paper has presented such type of real-time big data analytic applications and a classification of those applications. In addition, it presents the time requirements of each type of these applications along with its significant benefits. Also, a general overview of big data to describe a background knowledge on this scope.

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