Inference Engine
Securing Valued Data by using Encryption Algorithms with the help of Inference Engine and Knowledge Base
... This paper focuses on selecting the appropriate algorithm depending on the value of the data or information. This paper helps to secure the data based on the value, as if the data value is high, it needs to be more ...
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An agent based inference engine for efficient and reliable automated car failure diagnosis assistance
... ABSTRACT There are many difficulties and challenges involved in cars failure and malfunction diagnosis. The diagnosis process involves heuristic and complex series of activities and requires specific skills and ...
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Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities within the Home
... recognition engine based on a hierarchal structure, which allows modelling, representation and recognition of ADLs, their associated tasks, objects, relationships and ...the inference engine has been ...
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Crafting a Lightweight Bayesian Inference Engine
... This inference engine consists of the aforementioned four class types is implemented in Python programming language to be a reusable module as shown in Appendix ...probabilistic inference ...
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Geo calendar based Predictive Skyline Queries using Fuzzy Inference Engine
... All the previous studies gives the route planning trips based on network distances instead of travel time. Thus Predicted Skyline Query is finding the set of data objects by considering multiple query points to user ...
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DESIGNING FORWARD CHAINING INFERENCE ENGINE FOR FUZZY RULE BASED EXPERT SYSTEM FOR CYBER SECURITY
... 3. Defuzzification: It acts as the interface between the fuzzy logic control and the inference system, by providing the crisp output. Regular defuzzification methods are centroid, bisector, mean value of maximum ...
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A similarity based inference engine for non singleton fuzzy logic systems
... Fig. 1 illustrates the building blocks of a NSFLS which em- ploys a non-singleton fuzzifier for modelling the uncertainties embedded in the input. Here, in order to address uncertainty in the actual inputs, the fuzzifier ...
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MDSINE: Microbial Dynamical Systems INference Engine for microbiome time series analyses
... tems inference algorithms. The first of the two Bayesian inference algorithms, Bayesian Adaptive Lasso (BAL), is a regularization-based approach conceptually similar to the maximum likelihood ridge ...
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Design of Privacy Policy Inference Engine for Social Networking Sites
... This paper concentrates on As sharing individual media online gets to be less demanding and generally spread, new protection concerns rise – particularly when the [r] ...
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ACL Lifetime Achievement Award: The Brain as a Statistical Inference Engine—and You Can Too
... In Gibbs sampling we do not store the probabilities of all possibilities, but rather repeat- edly go through data making somewhat random choices based upon the program’s current “beliefs[r] ...
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Vague Reliability of a Network System Using Sugeno’s Fuzzy Failure Rates
... Abstract: In General classical sets are used to analyze the system Reliability. But due to uncertainty in the present era the classical reliability is inadequate enough to describe the real situation of the system. Fuzzy ...
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Dynamic Rule Modification Method For Rete-Eca Algorithm
... In the next access to the inference engine, a working memory element is updated. This update requires that the old instance of the element is removed from the system and the updated version of this element ...
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An Optimal Fuzzy Logic Guidance Law using Particle Swarm Optimization
... the Inference engine, the Fuzzy Knowledge base, and the ...the Inference engine converts the fuzzy input to a fuzzy ...the inference engine to crisp one using MFs analogous to ...
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Vol 3, No 2 (2017)
... transformed into fuzzy values by the fuzzifier in the Fuzzy Logic Controller (FLC). Each of the fuzzy values represents the degree of membership of the crisp value (i. e., the degree or extent to which the crisp value ...
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Dynamic Rule Modification Method For A Light-Weight Rule Engine
... rule-based inference, supervised learning, unsupervised learning, fuzzy logic, ontology, and probabilistic inference are ...rule-based inference method has been most used in various application areas ...
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A SURVEY ON ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEM
... The basic idea of this paper is to explore the artificial intelligence and to derived the expert system . How the artificial intelligence and expert system is correlated .what are further scope for the research of this ...
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Fast Neural Machine Translation Implementation
... Our second system uses multiplicative- LSTM (Krause et al., 2017) in the encoder and the first layer of a decder, and a GRU in the second layer, trained with an extension of the Nematus (Sennrich et al., 2017) toolkit ...
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Enhancing the Performance of Network Intrusion Detection System by Combining Naïve Bayes, Decision Tree and K Nearest Neighbors Algorithms
... the Inference Engine provides the predicting algorithms with test data which is used to compare with the learnt ...The Inference Engine also classify each record of the input data ...
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Intelligent System Stability using Type-2 Fuzzy Controller
... Fuzzy Inference Engine (FIE), Fuzzifier and Defuzzifier, these four components are worn to choose fuzzy rule which shows the human thinking, judgment and perception, to combine rules to develop a scaling ...
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An Expert System for Automated Essay Scoring (AES) in Computing using Shallow NLP Techniques for Inferencing
... separate Inference Engine and a separate Working Memory), one may choose to maintain each of these component parts as a separate application or module and improve on it, independent of the entire ...the ...
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