scholarly journals Weather Modeling Using Data-Driven Adaptive Rough-Neuro-Fuzzy Approach

2017 ◽  
Vol 12 (2) ◽  
pp. 429-435
Author(s):  
M. Sudha
Keyword(s):  
Intelligent Systems ◽  
Prediction Accuracy ◽  
Intelligent System ◽  
Data Driven ◽  
Fuzzy Approach ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Hybrid Data ◽  
Weather Modeling ◽  
Using Data

Recently, hybrid data-driven models have become appropriate predictive patterns in various hydrological forecast scenarios. Especially, meteorology has witnessed that there is a need for a much better approach to handle weather-related parameters intelligently. To handle this challenging issue, this research intends to apply the fuzzy and ANN theories for developing hybridized adaptive rough-neuro-fuzzy intelligent system. . Assimilating the features of ANN and FIS has attracted the rising attention of researchers due to the growing requisite of adaptive intelligent systems to solve the real world requirements. The proposed model is capable of handling soft rule boundaries and linguistic variables to improve the prediction accuracy. The adaptive rough-neuro-fuzzy approach attained an enhanced prediction accuracy of 95.49 % and outperformed the existing techniques.

A Gentle Introduction to Fuzzy Logic and Its Applications to Intelligent Agents Design

2011 ◽  
pp. 61-93
Author(s):  
Andre de Korvin
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Intelligent Agents ◽  
Fuzzy Systems ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Membership Functions ◽  
Neuro Fuzzy ◽  
Sugeno Model ◽  
Using Data

The purpose of this chapter is to present the key properties of fuzzy logic and adaptive nets and demonstrate how to use these, separately and in combination, to design intelligent systems. The first section introduces the concept of fuzzy sets and their basic operations. The t and s norms are used to define a variety of possible intersections and unions. The next section shows two ways to estimate membership functions, polling experts, and using data to optimize parameters. Section three shows how any function can be extended to arguments that are fuzzy sets. Section four introduces fuzzy relations, fuzzy reasoning, and shows the first steps to be taken to design an intelligent system. The Mamdami model is defined in this section. Reinforcement-driven agents are discussed in section five. Sections six and seven establish the basic properties of adaptive nets and use these to define the Sugeno model. Finally, the last section discusses neuro-fuzzy systems in general. The solution to the inverted pendulum problem is given by use of fuzzy systems and also by the use of adaptive nets. The ANFIS and CANFIS architectures are defined.

scholarly journals COVID-19 Risk Minimization Decision Making Strategy Using Data-Driven Model

2021 ◽  
Vol 3 (1) ◽  
pp. 57-66
Author(s):  
Akey Sungheetha
Keyword(s):  
Decision Making ◽  
Data Driven ◽  
Risk Minimization ◽  
Proposed Model ◽  
Epidemic Intelligence ◽  
Spread Dynamics ◽  
Using Data ◽  
The Impact ◽  
Global Strategies

In order to establish social resilient and sustainable cities during the pandemic outbreak, it is essential to forecast the epidemic trends and trace infection by means of data-driven solution addressing the requirements of local operational defense applications and global strategies. The smartphone based Digital Proximity Tracing Technology (DPTT) has obtained a great deal of interest with the ongoing COVID-19 pandemic in terms of mitigation, containing and monitoring with the population acceptance insights and effectiveness of the function. The DPTTs and Data-Driven Epidemic Intelligence Strategies (DDEIS) are compared in this paper to identify the shortcomings and propose a novel solution to overcome them. In terms of epidemic resurgence risk minimization, guaranteeing public health safety and quick return of cities to normalcy, a social as well as technological solution may be provided by incorporating the key features of DDEIS. The role of human behavior is taken into consideration while assessing its limitations and benefits for policy making as well as individual decision making. The epidemiological model of SEIR (Susceptible–Exposed–Infectious–Recovered) provides preliminary data for the preferences of users in a DPTT. The impact of the proposed model on the spread dynamics of Covid-19 is evaluated and the results are presented.

scholarly journals Linguistic Ontologies: Designing and Using in the Educational Intellectual Systems

2021 ◽  
Vol 4 (1) ◽  
pp. 97-111
Author(s):  
Olha Tkachenko ◽  
Kostiantyn Tkachenko ◽  
Oleksandr Tkachenko
Keyword(s):  
Computer Networks ◽  
Intelligent Systems ◽  
Semantic Analysis ◽  
Intelligent System ◽  
Subject Area ◽  
Intellectual System ◽  
Proposed Model ◽  
Small Set ◽  
Ontological Model ◽  
Linguistic Ontology

The purpose of the article is to investigate and consider the general trends, problems and prospects of designing and using linguistic ontologies in educational intellectual systems. The research methodology consists in semantic analysis methods of the basic concepts in the considered subject area (linguistic ontologies in the educational intellectual systems). The article discusses approaches to the use of linguistic models in modern educational intelligent systems. The novelty of the research is the analysis of the linguistic ontologies use in the educational intellectual systems. Conclusions. A model of linguistic ontology for the domain (disciplines “Computer Networks” and “Modelling Systems”) is presented. This model is used in the development of an educational intellectual system that supports online learning in these disciplines. The proposed model describes a set of relations of linguistic ontology, specially selected to describe the analyzed domain. To ensure these properties, it was proposed to use a small set of relationships. The proposed linguistic ontological model is implemented in an educational intelligent system that supports such disciplines as “Computer Networks” and “Modelling Systems”.

Agility of Supply Chain Management Solution Using Neural-Fuzzy Approach

2019 ◽  
Vol 16 (10) ◽  
pp. 4143-4148 ◽  
Author(s):  
Avinash Sharma ◽  
Aarti M. Karande ◽  
Dhananjay R. Kalbande
Keyword(s):  
Supply Chain ◽  
Business Process ◽  
Intelligent System ◽  
Business Environment ◽  
Rule Base ◽  
Fuzzy Approach ◽  
Computing Technique ◽  
Neuro Fuzzy ◽  
Soft Computing Technique ◽  
Unpredictable Environment

Enterprise solution is the architecture of collecting and processing business information. Business process agility affects process-based applications works as per changing business environment. This paper helps to understand different changing environment of business process in the supply chain domain. Changes depend on organizational policy; hence it can be incomplete or uncertain. To manage this unpredictable environment, a soft computing technique is used for constructing intelligent system. This paper shows use of Neuro-fuzzy approach to monitor agile behavior of the business process. Neural network phase is used for finding business process and parameter criticality. Fuzzy logic rule base phase calculates process agility based on the relation between process and it’s affecting parameter. Developed tool, shows that business architecture level is more prone to changes as compared to other architectural levels from the enterprise solution.

An Intelligent Approach to Assess Tacit Knowledge Fitness in Networked Enterprises

2011 ◽  
Vol 2 (2) ◽  
pp. 1-18
Author(s):  
Khalid A. Al-Mutawah
Keyword(s):  
Tacit Knowledge ◽  
Linguistic Variables ◽  
Fuzzy Approach ◽  
New Approach ◽  
Partnership Formation ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Assessment Approach ◽  
Intelligent Approach ◽  
Fuzzy Linguistic

Many organizations attempt to form strategic networked enterprises, yet such strategies are difficult to implement because they are as likely to fail as to succeed. This failure is due to intangible differences and mismatches between partners in tacit knowledge (TK). Despite the various proposed partnership assessment models/tools in the literature, an immediate need exists for a new approach to measure the mismatch in TK across different organizations. This is due to the complex, vague, and uncertain nature of TK attributes. Hence, an instrument for measuring vagueness (imprecise), such as fuzzy linguistic variables, is needed. In this study, the author applies a neuro-fuzzy approach to assess TK fitness in networked enterprises. The results show how differences in TK between partners affect the networked enterprise’s performance. Furthermore, the assessment approach reveals the most significant values to adopt and the irrelevant values that must be abandoned to smooth the partnership formation. The proposed model can prevent unexpected conflicts between partners if managed properly.

Diesel Engine Working Cycle Utilizing Artificial Intelligent Systems

2014 ◽  
Vol 490-491 ◽  
pp. 1057-1062
Author(s):  
Marwa Ahmed Abd-El Hamied
Keyword(s):  
Diesel Engine ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Cylinder Pressure ◽  
Artificial Intelligent ◽  
Engine Model ◽  
Working Cycle ◽  
Proposed Model ◽  
A New Technique ◽  
Artificial Neural Network Ann

In this paper a new technique is designed to build a model concerning cylinder pressure in diesel engine. The concept is to build a working cycle model utilizing artificial intelligent system. Artificial Immunity System (AIS) and Artificial Neural Network (ANN) are proposed as a new approach that can be used to simulate cylinder pressure for different crankshaft speed and loads. Experimental test results of diesel engine model (AD3.152 UR) are used to train AIS system and ANN. The proposed model succeeded to provide reliable result and prove to be useful in evaluating the quality of working cycle in diesel engine.

An Intelligent Approach to Assess Tacit Knowledge Fitness in Networked Enterprises

2013 ◽  
pp. 32-50
Author(s):  
Khalid A. Al-Mutawah
Keyword(s):  
Tacit Knowledge ◽  
Linguistic Variables ◽  
Fuzzy Approach ◽  
New Approach ◽  
Partnership Formation ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Assessment Approach ◽  
Intelligent Approach ◽  
Fuzzy Linguistic

Many organizations attempt to form strategic networked enterprises, yet such strategies are difficult to implement because they are as likely to fail as to succeed. This failure is due to intangible differences and mismatches between partners in tacit knowledge (TK). Despite the various proposed partnership assessment models/tools in the literature, an immediate need exists for a new approach to measure the mismatch in TK across different organizations. This is due to the complex, vague, and uncertain nature of TK attributes. Hence, an instrument for measuring vagueness (imprecise), such as fuzzy linguistic variables, is needed. In this study, the author applies a neuro-fuzzy approach to assess TK fitness in networked enterprises. The results show how differences in TK between partners affect the networked enterprise’s performance. Furthermore, the assessment approach reveals the most significant values to adopt and the irrelevant values that must be abandoned to smooth the partnership formation. The proposed model can prevent unexpected conflicts between partners if managed properly.

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