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With the flourish of online education and distance learning, it's become very important to make the evaluation in e-learning scientifically and objectively. This paper presents an intelligent fuzzy evaluation system based on our innovative evaluation method where management rules made by the experts are used to help, optimize and decide. On this basis, we develop an evaluation method and algorithm...
The aim of this work is to design an intelligent system for evaluating knowledge level of power plant operators who have completed training program. To build the evaluation system, skilled plant operator performance during fault conditions is simulated through expert system techniques. Rule based expert system developed, stores domain knowledge as set of rules. The system is integrated with Supervisory...
Credit point is the accumulation value of each item or activity that must be accomplished by instructor in Ministry of Manpower and Transmigration of Republic Indonesia. Instructors were facing difficulties in preparing credit point manually. Different understandings of the rules led error in the weighting of each activity assessed. Efficiency in the government operations has been a demand of institutional...
A system of communication, where at least one communicant is a machine, may be based on "Reverse Multiple-Choice Method," introduced by the present author for teaching and testing, that employs novel techniques based on the familiar multiple-choice format. The method may be used to train a machine for knowledge engineering and artificial intelligence, or for a trained machine to assist a...
Decision making in complex systems such as nuclear power plants is a difficult task at best. The nuclear power plant operators are susceptible to various operational mistakes causing the high risk accidents and safety issues. Therefore, the role of expert systems in the offline training program for the operators is ever increasing. In this paper, we describe the development of an Expert System Shell,...
We earlier introduced a novel framework for realization of Adaptive Autonomy (AA) in human-automation interaction (HAI). This study presents an expert system for realization of AA, using Support Vector Machine (SVM), referred to as Adaptive Autonomy Support Vector Machine Expert System (AASVMES). The proposed system prescribes proper Levels of Automation (LOAs) for various environmental conditions,...
The traditional expert system has shortcomings of poor self-learning ability, then expert system of diagnosis of jujube diseases and insects which is based on neural networks is designed. The related symptoms of jujube diseases and insect are collected and diagnosed by expert, the conclusion of the diagnostic process is regarded as the input neurons and output neurons of neural networks. After the...
By analyzing the character of oil equipment detection, the intelligent fusion model of detection information of oil equipment has been established. The feature-level fusion algorithm based on fuzzy neural network and expert system has been proposed, in which the expert system has been embedded into fuzzy neural network so that it could choose the membership function and adjust the network structure...
The complexity of humans and automation interaction in Smart Grid, as the future of power system, calls for embedding a level of intelligence in the system. Adaptive Autonomy (AA) theory is employed to manage high level complexity of the Human-Automation Interaction (HAI) system. The fuzzy expert system with Gradient Descent Algorithm (AAFGDES) is a data-driven approach applied to determine the Level...
There are some shortages of knowledge acquisition and inefficency in ES. So, combines ES with ANN to construst military equipment fault diagosis expert system. Introduces the neural network learning system, the knowledge base and the reasoning mechanism of the expert system. After introducing ANN and ES, utilizing the adapting, self-learning abilities of ANN, methods of knowledge acquirement and representation...
In this paper we employ backward Viterbi search for speech recognition. Contrary to forward Viterbi search that is performed from the beginning to the end, and where a word depends on the preceding words, backward Viterbi search is performed from the end to the beginning and the current word depends from the following words. As the errors of the forward and the backward searches are not the same,...
Kernel principal component analysis (KPCA) has been effectively applied as an unsupervised non-linear feature extractor in many machine learning applications and suggested for various data stream classification tasks requiring a nonlinear transformation scheme to reduce dimensions. However, the dimensionality reduction ability is restricted because of KPCA's high time complexity. So the practicality...
Due to massive date to be monitored for Metro shield machine, in order to solve the problems of knowledge acquisition bottlenecks and complexity structure of network structure and long traing time which based on expert system and neural network fault diagnosis methods. This article will introduces rough set theory to the subway shield machine fault diagnosis, Propose a method which based on rough...
Smart grid expectations objectify the need for optimizing power distribution systems greater than ever. Distribution Automation (DA) is an integral part of the SG solution; however, disregarding human factors in the DA systems can make it more problematic than beneficial. As a consequence, Human-Automation Interaction (HAI) theories can be employed to optimize the DA systems in a human-centered manner...
With the rapid development of science and technology, and the improvement of production safety and management standards, the use of expert system to bridge crane operator teaching simulation to train high quality personnel has become a pressing need. But it is hard to evaluate the train result. This paper aims at developing a bridge crane training system based expert system. The system includes some...
According to the complexity, variety and nonlinear mode of UAV system's faults, a combined method based on expert system and BP neural network was proposed for the diagnosis. Besides BP neural network, the design of the expert system based on BP neural network and its software implementation were depicted respectively. This method can overcome the insufficiency of traditional expert system such as...
In intensive aquaculture, the growing state of aquaculture organisms is affected by many factors. Among these factors, the quality of aquaculture water has a full impact on the growth of aquaculture organisms. High quality waters will be more conducive to the aquaculture organisms' growth. It can enhance the economic value of the aquaculture, and plays an important role in the aspect of developing...
This paper describes a co-evolutionary algorithm for generating simple spatially oriented tactics and considers whether students can learn better by playing against co-evolved opponents or by playing against an expert system or other similar hard-coded opponent. Although a number of artificially intelligent tutoring and e-learning systems exist, our work looks at using co-evolution to generate competent...
This paper proposes a novel inference method that is a combination of CBR (Case-based reasoning), grey theory and BP-ANN (Back propagation Artificial Neural Network). There are four basic steps in a typical CBR process: retrieving, reusing, revising and retaining. BP-ANN and grey theory are applied in retrieving to replace the traditional matching of similar cases. Before using the method to solve...
After having analyzed the factors of the mine flood of the coal floor, studied the theory of coal floor water bursting, and established the model library of mine flood forecast system, we finally designed the coal floor water bursting forecast system and make it to appliance from the surface to the point, with the help of GIS(Geographic Information System) spatial analysis tools and database management...
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