scholarly journals Novel Rule Base Development from IED-Resident Big Data for Protective Relay Analysis Expert System

10.5772/63756 ◽  
2016 ◽  
Author(s):  
Mohammad Lutfi Othman ◽  
Ishak Aris ◽  
Thammaiah Ananthapadmanabha
Keyword(s):  
Big Data ◽  
Expert System ◽  
Rule Base ◽  
Protective Relay

A new approximate belief rule base expert system for complex system modelling

2021 ◽  
pp. 113558
Author(s):  
You Cao ◽  
Zhijie Zhou ◽  
Changhua Hu ◽  
Shuaiwen Tang ◽  
Jie Wang
Keyword(s):  
Complex System ◽  
Expert System ◽  
Rule Base ◽  
System Modelling ◽  
Belief Rule Base

scholarly journals Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Expert System ◽  
Population Monitoring ◽  
High Definition ◽  
Contagious Diseases ◽  
The World ◽  
General Guide ◽  
The Impact ◽  
Back To Work

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.

scholarly journals Development of a Web Based Expert System for Rubber Crop Disease Diagnosis and Management

2018 ◽  
Vol 10 (3) ◽  
pp. 239-248
Author(s):  
S. Konyeha ◽  
F. A. Imouokhome
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Field Extension ◽  
Rule Base ◽  
Destructive Effect ◽  
Web Based ◽  
Procedural Code ◽  
Base Engine ◽  
Crop Disease ◽  
User Friendly

An expert system imitates the decision–making adeptness of a human expert. They are intended to answer complicated questions characterized mainly as if–then rules instead of traditional procedural code. A major problem facing the cultivation of rubber (Hevea brasiliensis) in developing countries is the destructive effect of pathogens which result in about fifty percent (50%) loss in crop yield. This problem persists, due to a communication gap between agricultural researchers, such that field extension officers, and farmers are hampered by various operational and logistic challenges. This paper is an effort to bridge this gap, and hence features an expert system that can be accessed online by farmers.  The expert system allows farmers to select disease symptoms presented in categories from a JAVA based user friendly graphical interface. The output generated by the rule–base engine, diagnoses the diseases of the rubber crop, and suggests curative and preventive measures. The main source of information for developing the expert system’ knowledge–base was the Rubber Research Institute, Iyanomo, Edo State, Nigeria.

scholarly journals Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads

2005 ◽  
Vol 5 (6) ◽  
pp. 821-832 ◽  
Author(s):  
A. Zischg ◽  
S. Fuchs ◽  
M. Keiler ◽  
G. Meißl
Keyword(s):  
Risk Management ◽  
Fuzzy Logic ◽  
Expert System ◽  
Temporal Variability ◽  
Hazard Index ◽  
Rule Base ◽  
Spatial And Temporal Variability ◽  
Snow Avalanches ◽  
System Behaviour ◽  
Wet Snow

Abstract. The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.

scholarly journals OPTIMALISASI PENERIMAAN REMUNERASI DOSEN MENGGUNAKAN METODE RULE BASE REASONING

2019 ◽  
Vol 6 (3) ◽  
pp. 224
Author(s):  
Samsudin Samsudin
Keyword(s):  
Expert System ◽  
Human Error ◽  
Work Performance ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Rule Base ◽  
Human Knowledge ◽  
Human Errors ◽  
Web Based ◽  
Web Based System

<p><em>Remuneration is a term that relates to employee payroll which is set by certain regulations routinely based on work values, with the aim of creating better and cleaner governance and increasing motivation and work performance. Performance is determined by assessing the compilation oflecturer’swork files and then verified by the department that responsible to it. Rule Base Reasoning is an expert system based on a series of rules that represent human knowledge and experience in solving some complex cases. Expert system is a system whose capability to adopt human knowledge in solving problems so the system can solve problems as is usually done by experts. To implement this method a web-based system is used using the PHP programming language with the concept of Object Oriented Programming with ecpectation this system can be designed more easily and can be developed continuously so it can optimize the acceptance of lecturer remuneration andso far it can minimize the possibility of errors due to human errors. on institutions and lecturers.</em></p><p><strong>Keywords</strong>: <em>Remuneration, Rule Base Reasoning, Performance, Lecturers, Expert Systems.</em><strong><em> </em></strong></p><p><em>Remunerasi merupakan sebuah istilah yang berhubungan dengan penggajian pegawai yang ditetapkan dengan peraturan tertentu secara rutin berdasarkan nilai-nilai kerja, dengan tujuan terciptanya tata kelola yang lebih baik dan bersih serta meningkatkan motivasi dan prestasi kerja.Kinerja ditentukan dengan pengumpulan bukti kerja kepada pihak yang bertanggung jawab dan dihitung oleh badan yang ditentukan.Rule Base Reasoning adalah sistem pakar berdasarkan serangkaian aturan-aturan yang merupakan representasi dari pengetahuan dan pengalaman manusia dalam memecahkan kasus yang rumit</em><em>. </em><em>Sistem pakar adalah suatu sistem yang berusaha mengadopsi pengetahuan manusia dalam menyelesaikan masalah sehingga sistem tersebut dapat menyelesaikan masalah seperti yang biasa dilakukan oleh para pakar</em><em>.</em><em>Untuk mengimplementasikan metode ini dibuat sebuah sistem berbasis web menggunakan bahasa pemrograman PHP dengan konsep Object Oriented Programming dengan harapan sistem ini bisa dirancang lebih mudah dan bisa dikembangkan secara berkelanjutan dan dapat mengoptimalkan penerimaan remunerasi dosen sehingga bisa memperkecil kemungkinan terjadinya kesalahan karena human error yang bisa menyebabkan kerugian pada pihak institusi maupun dosen.</em></p><p><strong>Kata kunci</strong>: <em>Remunerasi, Rule Base Reasoning, Kinerja, Dosen, Sistem Pakar.</em><strong></strong></p>

The Complementary Roles of Symbolic Computing and Numerical Optimization in Engineering Design Software

1987 ◽  
Author(s):  
R. Ellsworth ◽  
A. Parkinson ◽  
F. Cain
Keyword(s):  
Expert System ◽  
Engineering Design ◽  
Numerical Optimization ◽  
Optimization Methods ◽  
Design Rule ◽  
Rule Base ◽  
Design Problems ◽  
Symbolic Computing ◽  
Engineering Design Problems ◽  
Trial And Error Method

Abstract In many engineering design problems, the designer converges upon a good design by iteratively evaluating a mathematical model of the design problem. The trial-and-error method used by the designer to converge upon a solution may be complex and difficult to capture in an expert system. It is suggested that in many cases, the design rule base could be made significantly smaller and more maintainable by using numerical optimization methods to identify the best design. The expert system is then used to define the optimization problem and interpret the solution, as well as to apply the true heuristics to the problem. An example of such an expert system is presented for the design of a valve anti-cavitation device. Because of the capabilities provided by the optimization software, the expert system has been able to outperform the expert in the test cases evaluated so far.

A game-predicting expert system using big data and machine learning

2019 ◽  
Vol 130 ◽  
pp. 293-305 ◽  
Author(s):  
Wei Gu ◽  
Krista Foster ◽  
Jennifer Shang ◽  
Lirong Wei
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Expert System

The Design and Implementation of the Expert System for Cutting Parameters Based on CLIPS

2013 ◽  
Vol 385-386 ◽  
pp. 731-734
Author(s):  
Xue Bin Liu ◽  
Xi Bin Wang ◽  
Chong Ning Li ◽  
San Peng Deng
Keyword(s):  
Expert System ◽  
Cutting Parameters ◽  
Inference Engine ◽  
Knowledge Bases ◽  
Rule Base ◽  
Dynamic Link Library ◽  
Interactive Communication ◽  
Core Content ◽  
C Programming ◽  
Selection Of

Three core content of CLIPS expert system are researched on, namely rule base, fact base and inference engine. Using the production rules, in accordance with CLIPS syntax express the knowledge of cutting parameters, and according to the CLIPS syntax of the fact base, the rule base and the inference engine, knowledge bases of the cutting parameters expert system is built. In Visual C + + programming environment, combined with the CLIPS dynamic link library, by the interactive communication between Visual C + + and CLIPS, the software, cutting parameters expert system, has been developed successfully while has laid a good foundation for the selection of the cutting parameters to optimize.

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