Since many complex decision making problems can be solved solely by means of an appropriate algorithm, checking the quality of such algorithm is a key issue, even more relevant in the presence of fuzzy uncertainty. In...
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Since many complex decision making problems can be solved solely by means of an appropriate algorithm, checking the quality of such algorithm is a key issue, even more relevant in the presence of fuzzy uncertainty. In this paper we postulate that the design and formal specification of algorithms can be translated into a fuzzy framework introducing fuzzy first order logic and assert transformations. Following the classical crisp scheme we first formalize the concepts of a fuzzy algorithm specification and a fuzzy computing state, and then a new fuzzy computational logic is presented, so we can derive a computational reasoning for correctness of algorithms. A proposal for the evaluation and setting of suitable degrees of truth to computing states is also introduced.
fuzzy algorithms consisting of rules X(i)-->Y(i), i = 1,..., N, and for which a response to input X(i) is Y(i) are considered. A data structure and a rule of inference which make it possible are suggested.
fuzzy algorithms consisting of rules X(i)-->Y(i), i = 1,..., N, and for which a response to input X(i) is Y(i) are considered. A data structure and a rule of inference which make it possible are suggested.
In the past, the choices of beta values to be applied to find the beta-reducts in VPRS for an information system are somewhat arbitrary. In this study, a systematic method which bridges the fuzzy set methodology and p...
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In the past, the choices of beta values to be applied to find the beta-reducts in VPRS for an information system are somewhat arbitrary. In this study, a systematic method which bridges the fuzzy set methodology and probabilistic approach of RS to solve the threshold value beta determination problem in variable precision rough sets (VPRS) is proposed. Different from the existing probabilistic methods, the proposed method relies on the fuzzy membership degrees of each attribute of the objects to calculate beta. The proposed method gives the membership degrees and fuzzy aggregation operators the probabilistic interpretations. Based on the probabilistic interpretations, the threshold value beta of VPRS is directly derived from fuzzy membership degree by Implication Relations and fuzzy algorithms, in which the membership degrees are obtained by the standard fuzzy C-means method. The argument is that errors of system classification would occur in the fuzzy-clustering phase prior to information classification, therefore the threshold value beta should be constrained by the probability of belongingness of an object to the fuzzy clusters, i.e., through the values of membership functions. A few examples are given in the paper to demonstrate the differences with other beta-determining methods. (C) 2011 Elsevier Inc. All rights reserved.
This paper presents a new procedure for handling fuzzy algorithms. It consists of transforming the steps of a fuzzy algorithm into production rules of a fuzzy grammar, executing it using the dynamic of this grammar an...
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This paper presents a new procedure for handling fuzzy algorithms. It consists of transforming the steps of a fuzzy algorithm into production rules of a fuzzy grammar, executing it using the dynamic of this grammar and adjusting its execution by means of the learning capability of the fuzzy formal languages, with this method some flexible criteria about the goodness of the execution of a fuzzy algorithm are only necessary far adjusting it Finally, this procedure is applied for executing and adjusting a fuzzy rule-based system.
Traffic congestion in urban areas is a global challenge - leading to stifled economic growth, increased road accidents and atmospheric pollution, among other negative trends. Existing traffic management solutions have...
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ISBN:
(纸本)9781728134642
Traffic congestion in urban areas is a global challenge - leading to stifled economic growth, increased road accidents and atmospheric pollution, among other negative trends. Existing traffic management solutions have proven to be largely ineffective in medium-size African cities. Wireless sensor networks have emerged as possible cost-effective solutions, especially in under-developed countries. In this paper, we present a solution for detection and quantification of traffic congestion at signaled isolated four-way junctions in order to optimize traffic flow. The research utilizes optical sensors to collect road parameters and fuzzy logic to quantify and then prioritize entry. Simulations are used to compare strategies employed by traffic signals;the interest being to observe which of the two traffic light management schemes is more effective. The two schemes compared in this paper implement fairly weighted round-robin and fuzzy algorithms.
A smart city is a city concept who designed to help make it easy for people to access information and communication in their daily lives, with the Internet of things technology that helps to create electronic devices ...
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ISBN:
(纸本)9781728181967
A smart city is a city concept who designed to help make it easy for people to access information and communication in their daily lives, with the Internet of things technology that helps to create electronic devices connected to each other so that they can send data or do anything by reducing the function of humans. This research is to make the newest ideas in laundry services that support the development of smart cities, on IoT-based Smart Laundry on web applications that can simplify make the use of laundry more easier and more practical for users of laundry services on IoT-based Smart Laundry on web applications that can make it easier to use laundry services so that it will be saves more time and more practical for laundry service users. By using the fuzzy Algorithm as one of the Artificial Intelligence methods to support decision making in this system. This algorithm serves to make decisions in sorting which laundry will be picked up and also in this study the fuzzy Algorithm will produce the output to classify the price of laundry that will be paid by the user with the parameters of weight, humidity, and color. So, the laundry owner doesn't need to calculate manually again.
Future combat vehicles will implement hybrid energy management systems comprised of complex multivariable non-linear algorithms. In this paper, fuzzy algorithms based on neural networks (NNs) were applied to a hybrid ...
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ISBN:
(纸本)9781538674130
Future combat vehicles will implement hybrid energy management systems comprised of complex multivariable non-linear algorithms. In this paper, fuzzy algorithms based on neural networks (NNs) were applied to a hybrid energy management system. In addition, a combination of fuzzy theory and NN computing theory was analyzed in detail. fuzzy control algorithms were also used to resolve the run mode switch and power distribution issues of energy management systems. Furthermore, the proposed energy management control strategy was validated using MATLAB. The results of the simulation indicated that the proposed control strategy and algorithms could improve the working conditions and adaptability of future combat vehicles.
fuzzy logic is a convenient approach to construct maximum power-point tracking algorithms. A new scheme composed of two fuzzy systems is proposed here. The first fuzzy system is based on a modified hill climb search a...
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ISBN:
(纸本)9781424453610
fuzzy logic is a convenient approach to construct maximum power-point tracking algorithms. A new scheme composed of two fuzzy systems is proposed here. The first fuzzy system is based on a modified hill climb search algorithm to conclude the power set-point. The second fuzzy system is an adaptive PI-like controller that uses a variable structure tuning algorithm to track the power set-point. Simulations show that the proposed scheme can improve the system efficiency.
Profiling driving behavior has become a relevant aspect in fleet management, automotive insurance and eco-driving. Detecting inefficient or aggressive drivers can help reducing fleet degradation, insurance policy cost...
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ISBN:
(纸本)9781479912704;9781479912704
Profiling driving behavior has become a relevant aspect in fleet management, automotive insurance and eco-driving. Detecting inefficient or aggressive drivers can help reducing fleet degradation, insurance policy cost and fuel consumption. In this paper, we present a fuzzy-Logic based driver scoring mechanism that uses smartphone sensing data, including accelerometers and GPS. In order to evaluate the proposed mechanism, we have collected traces from a testbed consisting in 20 vehicles equipped with an Android sensing application we have developed to this end. The results show that the proposed sensing variables using smartphones can be merged to provide each driver with a single score.
Polysymptomatic time series are transformed to an one-dimensional interpretation space. The influence of psychic load is to estimate. This transformation is achieved by a structured fuzzy model. Each of the submodels ...
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Polysymptomatic time series are transformed to an one-dimensional interpretation space. The influence of psychic load is to estimate. This transformation is achieved by a structured fuzzy model. Each of the submodels is a fuzzy algorithm based on vague psychological statements. Different opinions among the specialists have to be modelled. These four models were applied to the same sets of data. It results in the preference of one of them.
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