Diffusion and economic growth fuzzy intelligent system based on DSGE model

2020 ◽  
pp. 1-9
Author(s):  
Shuqiang Liu ◽  
Dawei Zhao
Keyword(s):  
Economic Growth ◽  
Response Time ◽  
Intelligent System ◽  
Uncertain Data ◽  
Approximate Reasoning ◽  
Uncertain Information ◽  
Dsge Model ◽  
Actual Response ◽  
Evaluation Information ◽  
Rule Evaluation

In general, there are a lot of uncertainties in uncertain information, natural language, and human knowledge. The conclusion can be better deduced by using an approximate reasoning method, while a fuzzy intelligent system can deal with uncertain data and rule evaluation information systems. In order to better explore diffusion and economic growth, this paper constructs a fuzzy intelligent system based on the DSGE model and uses this system to analyze diffusion and economic growth. In order to verify the feasibility of this system, we test the response time and accuracy of the system. In addition, we also use the system to simulate diffusion and economic growth. The results show that with the increase of the task amount, the gap between the actual response time and the expected response time of the fuzzy intelligent system based on the DSGE model increases. When the task quantity is 20, the expected response time is 2.31 and the actual response time is 2.24. When the task quantity is 40, the expected response time is 2.5 and the actual response time is 2.36. The larger the task quantity is, the faster the response time of a fuzzy intelligent system based on the DSEG model is. Therefore, the fuzzy intelligent system based on the DSEG model has good performance and can analyze diffusion and economic growth well.

scholarly journals A New Evaluation Methodology for Quality Goals Extended by D Number Theory and FAHP

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 206
Author(s):  
Hongming Mo
Keyword(s):  
Number Theory ◽  
Process Management ◽  
Evidence Theory ◽  
Evaluation Methodology ◽  
Uncertain Information ◽  
Mathematical Tool ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Hierarchy Process ◽  
Evaluation Information

Evaluation of quality goals is an important issue in process management, which essentially is a multi-attribute decision-making (MADM) problem. The process of assessment inevitably involves uncertain information. The two crucial points in an MADM problem are to obtain weight of attributes and to handle uncertain information. D number theory is a new mathematical tool to deal with uncertain information, which is an extension of evidence theory. The fuzzy analytic hierarchy process (FAHP) provides a hierarchical way to model MADM problems, and the comparison analysis among attributes is applied to obtain the weight of attributes. FAHP uses a triangle fuzzy number rather than a crisp number to represent the evaluation information, which fully considers the hesitation to give a evaluation. Inspired by the features of D number theory and FAHP, a D-FAHP method is proposed to evaluate quality goals in this paper. Within the proposed method, FAHP is used to obtain the weight of each attribute, and the integration property of D number theory is carried out to fuse information. A numerical example is presented to demonstrate the effectiveness of the proposed method. Some necessary discussions are provided to illustrate the advantages of the proposed method.

scholarly journals A DSGE-VAR Analysis for Tourism Development and Sustainable Economic Growth

2020 ◽  
Vol 12 (9) ◽  
pp. 3635
Author(s):  
David Alaminos ◽  
Ana León-Gómez ◽  
José Ramón Sánchez-Serrano
Keyword(s):  
Economic Growth ◽  
Tourism Development ◽  
Dynamic Stochastic General Equilibrium ◽  
Long Term Effects ◽  
Dsge Model ◽  
External Effects ◽  
Dynamic Stochastic ◽  
Tourist Demand ◽  
Sustainable Economic Growth

This paper aims to provide a better basis for understanding the transmission connection between tourism development and sustainable economic growth in the empirical scenario of International countries. In this way, we have applied the dynamic stochastic general equilibrium (DSGE) model in different countries in order to check the power of generalization of this framework to study the tourism development. Also, we extend this model to obtain the long-term effects of tourism development with confidence intervals. The influence of tourism development on sustainable economic growth is proved by our results and show the indirect consequences between tourist activity and other industries produced through the external effects of investment and human capital and public sector. Our study confirms that the DSGE technique can be a generalized model for the analysis of tourism development and, especially, can improve previous precision results with the DSGE-VAR model, where vector autoregression (VAR) is introduced in the DSGE model. The simulation results reveal even more than when the productivity of the economy in general enhances, as the current tourist demand increases in greater proportion than more than the national tourism demand. For its part, the consumption of domestic tourism rises more than the consumption of inbound tourism if the productivity of the tourism production enhances, but non-tourism prices decrease at a slower rate and tourism investment needs a longer time to recover to what is established.

scholarly journals An Approach toward a Q-Neutrosophic Soft Set and Its Application in Decision Making

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 139 ◽  
Author(s):  
Majdoleen Abu Qamar ◽  
Nasruddin Hassan
Keyword(s):  
Decision Making ◽  
Uncertain Data ◽  
Real Life ◽  
Soft Set ◽  
Neutrosophic Set ◽  
Uncertain Information ◽  
Soft Sets ◽  
Independent Functions ◽  
Axis Of Symmetry ◽  
Set Aggregation

A neutrosophic set was proposed as an approach to study neutral uncertain information. It is characterized through three memberships, T , I and F, such that these independent functions stand for the truth, indeterminate, and false-membership degrees of an object. The neutrosophic set presents a symmetric form since truth enrolment T is symmetric to its opposite false enrolment F with respect to indeterminacy enrolment I that acts as an axis of symmetry. The neutrosophic set was further extended to a Q-neutrosophic soft set, which is a hybrid model that keeps the features of the neutrosophic soft set in dealing with uncertainty, and the features of a Q-fuzzy soft set that handles two-dimensional information. In this study, we discuss some operations of Q-neutrosophic soft sets, such as subset, equality, complement, intersection, union, AND operation, and OR operation. We also define the necessity and possibility operations of a Q-neutrosophic soft set. Several properties and illustrative examples are discussed. Then, we define the Q-neutrosophic-set aggregation operator and use it to develop an algorithm for using a Q-neutrosophic soft set in decision-making issues that have indeterminate and uncertain data, followed by an illustrative real-life example.

scholarly journals An Ideal Technique for Decision-Making Problems for Uncertain Data and Its Application In Medical Science

2019 ◽  
Vol 8 (11) ◽  
pp. 923-927
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Real World ◽  
Uncertain Data ◽  
Medical Science ◽  
Correlation Method ◽  
Uncertain Information ◽  
Neutrosophic Sets ◽  
Relation Database ◽  
Comparison Results

For representing and manipulating uncertain information like fuzzy, incomplete, inconsistent or imprecise, Neutrosophic relation database model is a more general platform, in the human decision-making process. Neutrosophic sets can easily handle real world problems. A new correlation method is introduced in this paper to construct similarity measure, by which decision making problem that exist in real world situation can be easily handled in regard of multiple existing criteria’s or incomplete or inconsistent information. The selection of the best option of alternative can be done by ranking all the other options as per similarity measure depending on concept of similarity. Later in this paper, an explanatory example is given of the proposed method and the comparison results are also presented to show the effective output.. The application in certain domains of medical diagnosis problems having multiple criteria’s in decision making are also discussed in the end of the proposed method.

scholarly journals RANCANG BANGUN SISTEM PENDETEKSI KEBAKARAN DINI BERBASIS LOGIKA FUZZY MENGGUNAKAN MULTISENSOR

2019 ◽  
Vol 4 (2) ◽  
pp. 46-57
Author(s):  
Nur Yanti ◽  
Fathur Zaini Rahman ◽  
Taufik Nur
Keyword(s):  
Temperature Sensor ◽  
Intelligent System ◽  
Fire Hazard ◽  
Sensor Reading ◽  
Fire Smoke ◽  
Multisensory System ◽  
Residential House ◽  
Smoke Sensor ◽  
House Fires ◽  
Rule Evaluation

At Indonesia, cases of residential house fires are still rampant. This resulted in considerable losses for the population of Indonesia. If there is no prevention or countermeasure, it is possible that the danger of a house fires will continue. Therefore, this system exists to create a condition where the system is able to detect the potential that will bring a fire hazard. In this system using a method that is the application of a multisensory system in detecting the presence of fire, smoke and temperature in the room. The sensors used include KY-026 fire sensor, MQ-9 smoke sensor and DS18B20 temperature sensor. Then the system also implements an intelligent system that is fuzzy logic to process sensor reading data. The three sensor inputs will be processed through the fuzzification stage, rule evaluation and the deffuzification. The output of this system is in the form of firm values, namely the values 1 to 5 from the results of the multisensory defuzzification in each module. So the error of the defuzzification average is 0.99% after being compared with the MATLAB output. This system is expected to be able to provide early warning of the threat of fire, reduce the risk of casualties, and be able to be implemented to a wider scale or scope.

A GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral considering risk preference

2020 ◽  
Vol 39 (3) ◽  
pp. 4285-4298
Author(s):  
Ran Tao ◽  
Fuyuan Xiao
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Choquet Integral ◽  
Risk Preference ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Human Knowledge ◽  
Mcdm Method ◽  
Evaluation Information

Group multi-criteria decision-making (GMCDM) is an important part of decision theory, which is aimed to assess alternatives according to multiple criteria by collecting the wisdom of experts. However, in the process of evaluating, because of the limitation of human knowledge and the complexity of problems, an efficient GMCDM approach under uncertain environment still need to be further explored. Thus, in this paper, a novel GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral is proposed. Firstly, since linguistic Z-numbers performs better in coping with uncertain information, it is used to express the evaluation information. Secondly, TOPSIS, one of the most useful and systematic multi-criteria decision-making (MCDM) method, is adopted as the framework of the proposed approach. Thirdly, frequently it exists interaction between criteria, so Choquet integral is introduced to capture this kind of influence. What’s more, viewing that decision makers (DMs) show different preferences for uncertainty, the risk preference is regarded as a vital parameter when calculating the score of linguistic Z-numbers. An application in supplier selection is illustrated to demonstrate the effectiveness of the proposed approach. Finally, a further comparison and discussion of the proposed GMCDM method is given.

scholarly journals A HYBRID MODEL FOR SHARING INFORMATION BETWEEN FUZZY, UNCERTAIN AND DEFAULT REASONING MODELS IN MULTI-AGENT SYSTEMS

2002 ◽  
Vol 10 (04) ◽  
pp. 401-450 ◽  
Author(s):  
XUDONG LUO ◽  
CHENGQI ZHANG ◽  
NICHOLAS R. JENNINGS
Keyword(s):  
Hybrid Model ◽  
Approximate Reasoning ◽  
Default Reasoning ◽  
Uncertain Reasoning ◽  
Uncertain Information ◽  
Multi Agent Systems ◽  
Unified Framework ◽  
Agent Systems ◽  
Special Cases ◽  
Multi Agent

This paper develops a hybrid model which provides a unified framework for the following four kinds of reasoning: 1) Zadeh's fuzzy approximate reasoning; 2) truth-qualification uncertain reasoning with respect to fuzzy propositions; 3) fuzzy default reasoning (proposed, in this paper, as an extension of Reiter's default reasoning); and 4) truth-qualification uncertain default reasoning associated with fuzzy statements (developed in this paper to enrich fuzzy default reasoning with uncertain information). Our hybrid model has the following characteristics: 1) basic uncertainty is estimated in terms of words or phrases in natural language and basic propositions are fuzzy; 2) uncertainty, linguistically expressed, can be handled in default reasoning; and 3) the four kinds of reasoning models mentioned above and their combination models will be the special cases of our hybrid model. Moreover, our model allows the reasoning to be performed in the case in which the information is fuzzy, uncertain and partial. More importantly, the problems of sharing the information among heterogeneous fuzzy, uncertain and default reasoning models can be solved efficiently by using our model. Given this, our framework can be used as a basis for information sharing and exchange in knowledge-based multi-agent systems for practical applications such as automated group negotiations. Actually, to build such a foundation is the motivation of this paper.

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