Intelligent manipulation technique for multi-branch robotic systems

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system

A Toolkit for uncertainty reasoning and representation using fuzzy set theory in PROLOG expert systems

This thesis examines the issue of uncertainty reasoning and representation in expert systems. Uncertainty and expert systems are defined. The value of uncertainty in expert systems as an approximation of human reasoning is stressed. Five alternative methods of dealing with uncertainty are explored. These include Bayesian probabilities, Mycin confirmation theory, fuzzy set theory, Dempster-Shafer\u27s theory of evidence and a theory of endorsements. A toolkit to apply uncertainty processing in PROLOG expert systems is developed using fuzzy set theory as the basis for uncertainty reasoning and representation. The concepts of fuzzy logic and approximate reasoning are utilized in the implementation. The toolkit is written in C-PROLOG for the PYRAMID UNIX system at the Rochester Institute of Technology

Fuzzy Expert System for Decision Making in Myocardial Infarction

Decision support system has been introduced in many domains and currently the computering world is focusing on decision support system with knowledge-bused. Knowledge system is one of the branches in artificial intellengence (AI), which incorporates human knowledge into the system us a result of knowledge acquistion process. Hybrid AI system, which is composed of multiple AI methods, has shown quite remarkable results in diagnosis and so far only a few of such approach has been done in known us FEMInS. This system integrates fuzzy logic technology with expert system, which helps the general medical practitioner to predict as well as diagnosing heart attack based on early symptons. Since fuzzy logic can be used for prediction and expert system can provide explanations and reasoning the combination of both fields is suitable for medical domain system, which generally needs to cater the problems of uncertainty and provide the explanation of the results to the user. FEMInS development has demonstrated that fuzzy logic can handle uncertainty better than expert system. This is due to the fact that fuzzy logic uses multi label and multi confidence value to reach the conclusion

Прогнозирование состояния объекта по результатам оценивания нечеткой экспертной системой

Предложена технология расчета аналитических описаний нечетких чисел, определяющих вероятности состояний объекта на момент прогноза, формируемых нечеткой экспертной системой. Описана процедура дефаззификации результатов прогнозирования.The calculation technology of analytical descriptions of fuzzy numbers which determining probabilities of the object’s states in the moment of prognosis in the fuzzy expert system is offered. The defuzzification procedure of the prognostication results is describe

Expert System as Tools for Efficient Teaching and Learning Process in Educational System in Nigeria, First Step

In educational field, many of the expert systems application are embedded inside the Intelligent Tuttoring System (ITS) by using techniques from adaptive hypertext and hypermedia. Most of the systems usually will assist student in their learning by using adaptation techniques to personalize with the environment, prior of student and students ability to learn in terms of technology, expert system in education has expanded very consistently from micro computer to web based (Woodin, 2001) and agent based expert system, it can provide an excellent alternative to private tutoring at anytime from any place (Markham, 2001) where internet is provided. Also agent based expert system surely will help users by finding materials from the web based on users profile. Supposedly, agent expert system should have capability to diagnose the users and giving the results according to the problems. Besides the use of expert system in technology, it also had tremendous changes in the applying of methods and techniques. Starting from a simple rule based system, currently expert system techniques had adapted a fuzzy logic (Starek, Tomer, Bhaskar, and Garcia, 2001) and hybrid based technique (Pretzas, Hatzilygeroudis, and Koutsojannis, 2001)

Intelligent System for Computer Aided Assembly Process Planning

This paper presents the concepts of the intelligent system for aiding of the module assembly technology. The first part of this paper presents a project of intelligent support system for computer aided assembly process planning. The second part includes a coincidence description of the chosen aspects of implementation of this intelligent system using technologies of artificial intelligence (artificial neural networks, fuzzy logic, expert systems and genetic algorithms)

Экспертное оценивание многофакторных рисков в технологическом предвидении

The multiple-factor risk evaluation in the technology foresight of prospects of the evolution of complex innovation systems is proposed. The risk of unpredictable situations and the force majeure risk are analyzed with the help of the modified BOCR AHP methodology. A system of indices for information risk evaluation on different information levels, such as point, interval and fuzzy expert estimates taking into account the probability distribution of expert information is developed

Adaptive Resonance Theory: Self-Organizing Networks for Stable Learning, Recognition, and Prediction

Adaptive Resonance Theory (ART) is a neural theory of human and primate information processing and of adaptive pattern recognition and prediction for technology. Biological applications to attentive learning of visual recognition categories by inferotemporal cortex and hippocampal system, medial temporal amnesia, corticogeniculate synchronization, auditory streaming, speech recognition, and eye movement control are noted. ARTMAP systems for technology integrate neural networks, fuzzy logic, and expert production systems to carry out both unsupervised and supervised learning. Fast and slow learning are both stable response to large non stationary databases. Match tracking search conjointly maximizes learned compression while minimizing predictive error. Spatial and temporal evidence accumulation improve accuracy in 3-D object recognition. Other applications are noted.Office of Naval Research (N00014-95-I-0657, N00014-95-1-0409, N00014-92-J-1309, N00014-92-J4015); National Science Foundation (IRI-94-1659

Application of fuzzy logic technique in medicine

The article presents a brief analysis of three areas of using of fuzzy logic technology in medicine: the fuzzy logic for making decisions in medical diagnostics based on a fuzzy expert system, a fuzzy inference system for remote monitoring of vital functions and a healthcare system for individual physiological monitoring using a wireless body network with a routing algorithm based on the fuzzy logic

A Review on Expert System Applications in Power Plants

The control and monitoring of power generation plants is being complicated day by day, with the increase size and capacity of equipments involved in power generation process. This calls for the presence of experienced and well trained operators for decision making and management of various plant related activities. Scarcity of well trained and experienced plant operators is one of the major problems faced by modern power industry. Application of artificial intelligence techniques, especially expert systems whose main characteristics is to simulate expert plant operator’s actions is one of the actively researched areas in the field of plant automation. This paper presents an overview of various expert system applications in power generation plants. It points out technological advancement of expert system technology and its integration with various types of modern techniques such as fuzzy, neural network, machine vision and data acquisition systems. Expert system can significantly reduce the work load on plant operators and experts, and act as an expert for plant fault diagnosis and maintenance. Various other applications include data processing, alarm reduction, schedule optimisation, operator training and evaluation. The review point out that integration of modern techniques such as neural network, fuzzy, machine vision, data base, simulators etc. with conventional rule based methodologies have added greater dimensions to problem solving capabilities of an expert system.DOI:http://dx.doi.org/10.11591/ijece.v4i1.502