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Applied machine learning and management of volatility, uncertainty, complexity & ambiguity (V.U.C.A)
2020
Journal of Intelligent & Fuzzy Systems
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a control strategy of permanent magnet-oriented field synchronous motor based on intelligent fuzzy control system and generalized predictive control with non-linear identification. ...
They have proposed a method based on fuzzy logic control and neural network algorithm to analyse the high frequency dynamic characteristics of ballast less track wheelrail vehicle system. ...
The next paper entitled, "Optimization of Architectural Art Teaching Model Based on Naive Bayesian Classification Algorithm and Fuzzy Model", by Ying Liu, proposed a new hybrid architectural art teaching ...
doi:10.3233/jifs-179915
fatcat:njwjogoperg2jggdkyheiibbhi
Edge computing-oriented smart agricultural supply chain mechanism with auction and fuzzy neural networks
2024
Journal of Cloud Computing: Advances, Systems and Applications
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We formulated invisible auction mechanisms that hide actual bid values and regulate information flows, combined with machine learning techniques for robust predictive analytics. ...
While rule-based fuzzy systems encode domain expertise in agricultural decision-making, adaptable training algorithms help optimize model parameters from the data. ...
Fuzzy inventory controllers allow the embedding of domain insights and adaptive calibration. ...
doi:10.1186/s13677-024-00626-8
fatcat:cu2gxmahs5d6bkhbkmbrn7hzri
Using attribute and attitude assessment for bidding in automated auctions
2009
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services - iiWAS '09
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The overall assessment is used to determine a price range based on current bid, which finally selects the best one as the new bid. ...
The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process as well use heuristic rules to determine attitude of bidding agents in simulated auctions to procure ...
It uses fuzzy reasoning techniques to predict closing price of auctions, fuzzy recognition to assess the degree of competitiveness in the prevailing market context, anf fuzzy set technique to control bidding ...
doi:10.1145/1806338.1806407
dblp:conf/iiwas/GoyalZ09
fatcat:p3bfufydrzhqzfb3qz4x4mlygy
Design and analysis of experiments in ANFIS modeling for stock price prediction
2011
International Journal of Industrial Engineering Computations
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In this paper, we implement the design of experiment (DOE) technique to identify the significant parameters in the design of adaptive neuro-fuzzy inference systems (ANFIS) for stock price prediction. ...
ANN learning algorithms can be employed for optimization of parameters in a fuzzy system. ...
However, fuzzy systems do not provide a mechanism to tune those rules. On the other hand, NN are adaptive systems that can be trained and tuned from a set of input-output data set. ...
doi:10.5267/j.ijiec.2011.01.001
fatcat:hks4fefyrjhmzckvrmu7lgkone
An Approach on Multilateral Automated Negotiation
2015
Procedia Computer Science
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We have studied fuzzy inference logic based system, multithreading based automated negotiation system, linear programming based system and genetic algorithm based system and we have compared some methods ...
Peer-review under responsibility of organizing committee of the 4th International Conference on Advances in Computing, Communication and Control (ICAC3'15). ...
Intelligent techniques such as neural networks, genetic programming, fuzzy logic theory and Bayesian theory are used to learn opponent's behaviour, decision-making and generating offers and fuzzy system ...
doi:10.1016/j.procs.2015.04.256
fatcat:qt3herhdzfhwta52u2abnxjq2y
Hybrid soft computing systems: industrial and commercial applications
1999
Proceedings of the IEEE
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We illustrate some combinations of hybrid SC systems, such as fuzzy logic controllers (FLCs) tuned by neural networks (NNs) and evolutionary computing (EC), NNs tuned by EC or FLCs, and EC controlled by ...
We present a collection of methods and tools that can be used to perform diagnostics, estimation, and control. ...
Thus evolutionary algorithms can evolve a fuzzy controller by using a fitness function based on such a cost function. Many researchers have explored the use of EC to tune fuzzy logic controllers. ...
doi:10.1109/5.784245
fatcat:ntpjdm3exbgudlxqi62ikvsvuu
Designing a Successful Trading Agent: A Fuzzy Set Approach
2004
IEEE transactions on fuzzy systems
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He helped pioneer the use of agent-based techniques for real-world applications and has also made theoretical contributions in the areas of automated negotiation and auctions, cooperative problem solving ...
He has published some 200 articles on various facets of agent-based computing, and is in the top 125 most cited computer scientists (according to the citeseer digital library). Prof. ...
Luck who went to the U.S. to present our agent at TAC-01 on very short notice, Y. Z. Wei who helped with agent connecting problems and monitoring the seeding round games in TAC-02, A. J Riddoch, J. ...
doi:10.1109/tfuzz.2004.825064
fatcat:fknn4cfoufhntoqts77q75p33q
Introductory Chapter: Customer Satisfaction Alignment with "On the Edge" IT Tools
[chapter]
2020
Customer Relationship Management and IT
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7 Introductory Chapter: Customer Satisfaction Alignment with "On the Edge" IT Tools DOI: http://dx.doi.org/10.5772/intechopen.91200 ...
Stochastic graph models for customer lifecycle and behavior prediction In this section I deliver the stochastic graph model [5] , which controls a userticket buyer-behavior at the ticket-selling Website ...
As a result, the stochastic graph model can adjust the ticket system behavior according to the user's behavior based not only on previous statistical data but on the probability of his/her behavior in ...
doi:10.5772/intechopen.91200
fatcat:6evvayhtybeftno22tvzzubewq
Application Of Fuzzy Regression Model For Real Estate Price Prediction
2016
Malaysian Journal of Computer Science
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In this paper, we propose a fuzzy least-squares regression-based (FLSR) model to predict the prices of real estates. ...
A comprehensive comparison studies in terms of prediction accuracy and computational complexity of ANN, Adaptive Neuro Fuzzy Inference System (ANFIS) and FLSR has been carried out. ...
Authors in [10] undertook a comparison of four techniques (i.e., MRA, ANN, Memory-based Reasoning and Fuzzy Logic) for estimating house value. ...
doi:10.22452/mjcs.vol29no1.2
fatcat:3infr4bk6nbyxmovogouzwwxgy
Decisión Making in Multi-lssue e-Market Auction Using Fuzzy Techniques and Negotiable Attitudes
2008
Journal of Theoretical and Applied Electronic Commerce Research
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Our agent also uses fuzzy techniques for the decision making: to make decisions about the outcome of auctions, and to alter the agent's bidding strategy in response to the different criteria and market ...
It shows that agents' bidding strategy explore the attitudes and behaviors that help agents to manage dynamic assessment of prices of goods given the different criteria and scenario conditions. ...
Cohen and Levesque [7] , on the other hand, developed a logic in which intention is defined. ...
doi:10.4067/s0718-18762008000100009
fatcat:44wl6ansxrhk7gcgd63ddvcg3a
Trust Management Techniques and their Challenges in Cloud Computing: A Review
2022
International Journal of Computer Networks And Applications
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Cloud computing is a way to handle tasks like development, production, and maintenance done on the web. This domain is evolving. ...
This report includes a systematic review of various high-quality articles published on trust management between 2010 and July 2022. ...
Subjective Logic Theory It is a strategy for managing uncertainty. It functions based on opinions and worldviews. Subjective logic is a kind of belief theory and regression analysis. ...
doi:10.22247/ijcna/2022/217708
fatcat:lct43dysgnbfflsg6kri6gham4
Fuzzy Approach to Decision Support System Design for Inventory Control and Management
2017
Journal of Intelligent Systems
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The model of the DSS reported here is based on a framework commonly known as adaptive neuro-fuzzy inference system (ANFIS), which is a version of NFS. ...
The configured model has the advantages of both the ANN and fuzzy systems, and has been tested for the design of a DSS for use as part of inventory control. ...
In many situations, DSS related to inventory control is deployed in situations where there are innumerable uncertainties in terms of buyer and seller behavior, factors linked with production and transportation ...
doi:10.1515/jisys-2017-0143
fatcat:d3rtrwxgvjgvbccpaizdqnk7oe
A Survey of Quality of Service in Multi-tier Web Applications
2016
KSII Transactions on Internet and Information Systems
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Recently, a number of rule-and model-based approaches have been designed for dynamic resource management in virtualized data centers. ...
This survey investigates the challenges of resource provisioning and provides a competing assessment on the existing approaches. ...
The rule-based approaches based on action selection include fuzzy control logic, reinforcement, and static machine learning. ...
doi:10.3837/tiis.2016.01.014
fatcat:olcm4bcazjh7havualoqbzcaga
Comfort Evaluation of Wearable Functional Textiles
2021
Materials
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A brief review of clothing comfort evaluations for textile fabrics based on subjective and objective techniques was conducted. ...
For textile-based materials which have close contact to the skin, clothing comfort is a fundamental necessity. ...
However, fuzzy logic has its own limitations as it does not have a specified technique that can be used as a mentor in the process of translating human perception into a rule-based fuzzy inference system ...
doi:10.3390/ma14216466
pmid:34771993
pmcid:PMC8585350
fatcat:rzksfo4qgbfbzaa2l7o62gjubi
KNOWLEDGE-BASED FIS AND ANFIS MODELS DEVELOPMENT AND COMPARISON FOR RESIDENTIAL REAL ESTATE VALUATION
2018
International Journal of Strategic Property Management
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This study was established to investigate the usability of the expert knowledge based fuzzy logic methodology in determining real-estates values. ...
The memberships were established with poll analysis and were rule based on expert knowledge. The model structure was formed by using the Mamdani structure in the MATLAB fuzzy toolbox. ...
Fuzzy Logic controls unclearly defined systems by sorting them with a commonsensical approach. ...
doi:10.3846/ijspm.2018.442
fatcat:m63nxcizrjcghozcz6kghd2fgq
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