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In this paper using BP neural network as core algorithm, Java and MATLAB as development tools, build a fault intelligent analysis system of electric energy data acquire network which have machine self-learning ability. This diagnosis system adopts the model of cloud computing in structure, artificial intelligence calculation in the cloud, friendly humancomputer interaction at the front-end. Lab simulation...
Past AI systems were domain specific intended to fulfill a particular task. These days, there is a need for versatile machines that are capable of performing multiple tasks, should be adaptive in nature and should have decision-making capabilities for any situation. At this point, the role of Cognitive Computing comes into the picture. Cognitive computing is a promising area of research, it is depicting...
This paper introduces five similarity measures, very well known in literature, but not because of using them to compare rules between themselves and choose the most similar one. Rules in knowledge bases are a very specific type of data representation and it is necessary to compare them carefully. The goal of the paper is to analyze the influence of using different similarity measures on the number...
Development problems of the information systems analysis and design for monitoring the status of large-scale infrastructural objects in the categorical models systems have been considered at this article. The formal apparatus of a multilevel knowledge representation on the basis of the categorical approach, the theory of computational models, knowledge representation production systems was described...
In order to answer effectively on behalf of humans in a DeepQA environment, such as the American quiz show Jeopardy (http://www.jeopardy.com), the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. Many existing spatial reasoners share a common limitation in that they do not contain conversion rules between the directional...
We introduce Venn diagrams for multisets and showhow they simplify the analysis of multisets. Venn diagrams arevery useful in proofs involving multisets and multiset orders, especially considering the complications introduced by the multiplicity of elements in multisets. We compare the Venn diagramsfor multisets with the corresponding ones for sets. Thus, wepresent two types of Venn diagrams for multisets,...
Representing human knowledge plays an important role in artificial intelligence science. Nowadays, there are many effective methods for representing knowledge such as semantic networks, conceptual graphs, computational networks. Computational Objects Knowledge Base (COKB) can be used to represent knowledge in many kinds of knowledge domain, such as Linear Algebra, Analytic Geometry, Direct Current...
Dimensionality reduction is the important topic for data mining and pattern recognition. Many dimensionality reduction methods for complex massive data have been proposed. Due to massive data have many kinds of data such as: noise, inconsistent and incomplete information. The dimensionality reduction task is difficult; to date, there are no efficient approaches for dimensionality reduction in complex...
CogPrime, a comprehensive architecture for embodied Artificial General Intelligence, is reviewed, covering the core architecture and algorithms, the underlying conceptual motivations, and the emergent structures, dynamics and functionalities expected to arise in a completely implemented CogPrime system once it has undergone appropriate experience and education. A qualitative argument is sketched,...
Planning suitable menus for individuals who have health problems is a complex task since the solutions produced by professionals (dietitians) are usually very subjective and difficult to be systematically represented. This research focused on designing the knowledge base repository construction which consists of the existing cases to be used as the case-based for the retrieval process. The main aim...
This paper is dedicated to two seemingly different problems. The first one concerns information theory and the second one is connected to logic synthesis methods. The reason why these issues are considered together is the important task of the efficient representation of data in information systems and as well as in logic systems. An efficient algorithm to solve the task of attributes/arguments reduction...
Intelligence analysis in a counter-insurgency (COIN) environment requires the consideration of many sources of information which are continuously reporting on the current state of the world. Methods to incorporate the uncertainties present in these sources of information have been identified and implemented within a graph matching algorithm, which provides a situation assessment. Thus far, the methods...
The modern state of the art planners are highly effective and has strong handing capability, but most of them can't learn anything from previous experiences. In the past there have been many researches on learning problem in planning and make some progress. However, the knowledge used in these methods is not easy to learn and use such that Learning can often make performance degrade, learning did...
In order to realize the objective and synthetic evaluation of the feasibility in Low-carbon (LC) project, the paper constructs the knowledge representation system(i.e. attribute value of information system), applies the reduction and the mining rules of the Rough Set Theory, at same the time computing dynamic weight, subjective weight, objective weight are combined with Analytic Hierarchy Process...
The difficulties encountered in sequential decision-making problems under uncertainty are often linked to the large size of the state space. Exploiting the structure of the problem, for example by employing a factored representation, is usually an efficient approach but, in the case of partially observable Markov decision processes, the fact that some state variables may be visible has not been sufficiently...
Knowledge representation is a key area of research in artificial intelligence which deals with the proper storage and retrieval of knowledge for various useful applications. This research paper proves that knowledge can be easily and efficiently represented in predicate logic. The algorithm in this paper splits the Urdu text/sentences into phrases/constituents and then represents these in predicate...
It is important to integrate contextual information in order to improve the performance of automatic image annotation. Graph based representations allow incorporation of such information. In this paper, we propose a graph-based approach to automatic image annotation which models both feature similarities and semantic relations in a single graph. The annotation quality is enhanced by introducing graph...
Nowadays, Exploring and extracting knowledge from data is one of the fundamental problems in science. while many data mining models concentrate on automation and efficiency, interactive data mining models focus on adaptive and effective communications between human users and computer systems. User views, preferences, strategies play the most important roles in human-machine inter activities, guide...
Concept lattice is accurate and complete in knowledge representation and is an effective tool for data analysis and knowledge discovery. This paper focuses on incremental computation of intent reduction of concepts. By theoretical analysis of characteristic change of intent reduction of lattice nodes during incremental construction of concept lattice, it advances an incremental algorithm to compute...
To find the implied dependency relationships and knowledge representation from sample data, a Bayesian Network structure learning method was proposed on the basis of ant colony algorithm, which provided support for the modeling of complex decision-making tasks. Algorithm design was presented after the formal description of Bayesian network structure learning problems. Accordingly, a Bayesian network...
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