Generally speaking, Karnik-Mendel algorithm is a standard way to calculate the centroid and perform type-reduction (TR) for interval type-2 fuzzy sets and systems. In this paper, an efficient centroid type-reduction s...
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Generally speaking, Karnik-Mendel algorithm is a standard way to calculate the centroid and perform type-reduction (TR) for interval type-2 fuzzy sets and systems. In this paper, an efficient centroid type-reduction strategy for general type-2 fuzzy sets is introduced based on Karnik-Mendel (km) algorithm, enhanced Karnik-Mendel (Ekm) algorithm, enhanced iterative algorithm+stopping condition (EIASC). The strategy uses the result of alpha-plane representation, performs the centroid type-reduction on each alpha-plane, and expands type-reduction algorithms for general type-2 fuzzy logic systems. Simulations performed and compared by each of three types of algorithms show that they usually need only several resolution of alpha values such that the defuzzified values converge to real values. Compared with the exhaustive computation method, the method can tremendously decrease the computation complexity from exponential into linear. So it provides the potential application value for general type-2 fuzzy logic systems.
Relay is a type of application of Device-to-Device (D2D) communication which could optimize the system capacity over the shared uplink (UL) resources while fulfilling prioritized cellular service constrains. In this p...
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ISBN:
(纸本)9781612846835;9781612846828
Relay is a type of application of Device-to-Device (D2D) communication which could optimize the system capacity over the shared uplink (UL) resources while fulfilling prioritized cellular service constrains. In this paper, we consider D2D communication for relay purpose assists User Equipments (UEs) to communicate with Base Station (BS). For constraining the interference from D2D communication to cellular communication in the permitted range by system, we analyze the transmission rate from D2D UE. Further, we deduce a relay selection rule based on the interference constraining. Then, we apply the km algorithm and the greedy algorithm as two types of selection methods to select different relay for every relay-needed UE according to the selection rule. The numerical simulations results show the sum-rate can be improved by selecting the relays according to the selection rule, and km algorithm achieves a slightly higher sum-rate than that of greedy algorithm based on the relay selection rule.
A sort method is proposed to enhance the significant spectral components of test set. In the field of integrated circuit testing, to calculate significant spectral components, it's necessary to do spectrum analysi...
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ISBN:
(纸本)9781509040940
A sort method is proposed to enhance the significant spectral components of test set. In the field of integrated circuit testing, to calculate significant spectral components, it's necessary to do spectrum analysis for the test set. In this paper, a bipartite graph and weight matrix are constructed based on the test set and its significant spectral components. Therefore, the problem of enhancement of significant spectrum components is transformed into a bipartite graph matching problem that can be solved by km (Kuhn-Munkras) algorithm. After the order adjustment of the test set according to the matching relationship, the correlation between the significant component and test set has been increased, and the significant spectral components are enhanced. Finally, the experimental results on the test set of the ISCAS-89 benchmark circuits show that the coefficients of the sorted test have increased by 9.47% on average, and the incompatible bits between the test set and its significant spectral components have effectively reduced by 14.18% on average.
Logistics order distribution is an important part of the sales process of finished steel products, and plays a vital role in the overall experience of the sales process and the virtuous cycle of the whole process. In ...
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ISBN:
(纸本)9781450397773
Logistics order distribution is an important part of the sales process of finished steel products, and plays a vital role in the overall experience of the sales process and the virtuous cycle of the whole process. In the actual production process, the manual order distribution model maintained for a long time seems to have a richer accumulation of experience and knowledge, but in reality it has become difficult to adapt to the development requirements of a long time dimension. In order to fully consider the lowest logistics cost of sales in a time cycle as well as the higher revenue of the carrier driver, while ensuring the long-term revenue of the enterprise, this paper considers multi-objective constraints, establishes Markov decision model, introduces km algorithm to perform dichotomous graph matching, based on the multi-objective optimization for maximizing driver revenue and minimizing enterprise cost, with the long-term ultimate goal of maximizing total steel commodity transaction volume, and finally Combining the value function and the multi-objective optimization function of multiple attributes to form a complete matching decision of vehicles and goods. Using real business data of steel enterprises as an example, the data is pre-processed and then suitable features are screened for model training and the correctness and usability of the algorithm is verified. The results show that the model can better address the needs of steel companies in order allocation scenarios compared to traditional order allocation methods.
The linguistic weighted average (LWA) is an extension of the fuzzy weighted average (FWA).The process of solving LWA can be divided into steps of solving two ***, the commonly used method of FWA is based on α-cut dec...
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The linguistic weighted average (LWA) is an extension of the fuzzy weighted average (FWA).The process of solving LWA can be divided into steps of solving two ***, the commonly used method of FWA is based on α-cut decomposition,which discretizes the [0, 1] interval into several α-cuts and then computes each α-cut as an interval weighted ***, this method involves large amount of calculations, and the result for LWA is not *** this paper, we adopt a new algorithm, analytical solution methods, which is more accurate and *** the end of this paper, we present a numerical example to illustrate the algorithm.
The linguistic weighted average(LWA) is an extension of the fuzzy weighted average(FWA). The process of solving LWA can be divided into steps of solving two ***,the commonly used method of FWA is based onα-cut decomp...
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The linguistic weighted average(LWA) is an extension of the fuzzy weighted average(FWA). The process of solving LWA can be divided into steps of solving two ***,the commonly used method of FWA is based onα-cut decomposition, which discretizes the[0,1]interval into several a-cuts and then computes eachα-cut as an interval weighted ***,this method involves large amount of calculations,and the result for LWA is not *** this paper,we adopt a new algorithm, analytical solution methods,which is more accurate and *** the end of this paper,we present a numerical example to illustrate the algorithm.
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