In this paper, we improve a very famous algorithm Apriori for data mining. Algorithm Apriori is to mine motifs, i.e., maximal frequent patterns or itemsets. The algorithm assumes that all items are totally ordered, e....
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ISBN:
(纸本)9789812799463
In this paper, we improve a very famous algorithm Apriori for data mining. Algorithm Apriori is to mine motifs, i.e., maximal frequent patterns or itemsets. The algorithm assumes that all items are totally ordered, e.g., A < B < C < D < for items A,B,C,D etc. Furthermore, items within an itemset are sorted in lexicograghic order. We improve the algorithm, present a new one without assuming any ordering. The new algorithm looks sound and more efficient.
We investigate interpretations parallel to psi parallel to(D), of formulas psi of a first order fuzzy logic in models D which are based on objects of a category SetF(Omega) which consists of Omega-seys, i.e. sets with...
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ISBN:
(纸本)9789812799463
We investigate interpretations parallel to psi parallel to(D), of formulas psi of a first order fuzzy logic in models D which are based on objects of a category SetF(Omega) which consists of Omega-seys, i.e. sets with similarity relations with values in a complete MV-algebra Omega. These interpretations are fuzzy sets in an Omega-set (A, delta), i.e. a morphism (A, delta) --> (Omega, <->) in a category SetF(Omega). We show that if phi : D-1 --> D-2 is a strong homomorphism between two models then there are also strong relationships between interpretations parallel to psi parallel to(D1), and parallel to psi parallel to(D2). Finally, for any model D based on an Q-set (A, delta) we construct another model F(D) based on a set F(A, delta) of all fuzzy sets in (A, delta) and such that a singleton map {-} is a strong model homomorphism D --> F(D).
When we deal with group decision making (GDM) situations with incomplete preference relations, there exist cases in which the classical selection procedure (aggregation and exploitation) could not be applied satisfact...
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ISBN:
(纸本)9789812799463
When we deal with group decision making (GDM) situations with incomplete preference relations, there exist cases in which the classical selection procedure (aggregation and exploitation) could not be applied satisfactorily. For example, we could find that some preference degrees of the collective preference relation cannot be computed in the aggregation phase and consequently, the ordering of some alternatives cannot be computed in the exploitation phase. To overcome this problem, we present a selection process for GDM with incomplete 2-tuple fuzzy linguistic preference relations that requires three phases: (1) estimation phase of missing values, (2) aggregation phase and (3) exploitation phase.
Triangle Logic is a formal fuzzy logic with intervals as truth values. Its construction is based on triangle algebras: equationally defined structures that are equivalent with certain residuated lattices on a set of i...
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ISBN:
(纸本)9789812799463
Triangle Logic is a formal fuzzy logic with intervals as truth values. Its construction is based on triangle algebras: equationally defined structures that are equivalent with certain residuated lattices on a set of intervals, which were called interval-valued residuated lattices (IVRLs). We prove that the so-called pseudo-prelinear triangle algebras are subdirect products of pseudo-linear triangle algebras. This can be compared with MTL-algebras (prelinear residuated lattices) being subdirect products of linear residuated lattices, Using this result, we prove an analogue of the chain completeness of MTL for Pseudo-prelinear Triangle Logic. It also enables us to prove properties of pseudo-prelinear triangle algebras more easily. We give some examples.
We expand the classical model of a two-player game by inserting of fuzzy sets as payoff values in the game matrix. Players can thus formulate their payoff expectations with words instead of deciding on numerical entri...
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ISBN:
(纸本)9789812799463
We expand the classical model of a two-player game by inserting of fuzzy sets as payoff values in the game matrix. Players can thus formulate their payoff expectations with words instead of deciding on numerical entries of the matrix. In this way we count on the better verbal communication between players when designing the preliminaries of the game. As a final result we expect to obtain samples of the players' optimal strategies, which will preserve the profit of the game on the neutral level.
The paper addresses a hybrid technology upon that a decision support system (DSS) for disaster response is built. The hybrid technology combines intelligent technologies of profiling, ontology engineering and manageme...
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ISBN:
(纸本)9789812799463
The paper addresses a hybrid technology upon that a decision support system (DSS) for disaster response is built. The hybrid technology combines intelligent technologies of profiling, ontology engineering and management, context management, constraint satisfaction, and Web Services. The application of the hybrid technology is illustrated by an example of real-time resource coordination for logistics management during fire response operations.
On-line sensor monitoring allows detecting anomalies in sensor operation and reconstructing the correct signals of failed sensors, Since in field applications the number of signals to be monitored is often too large t...
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ISBN:
(纸本)9789812799463
On-line sensor monitoring allows detecting anomalies in sensor operation and reconstructing the correct signals of failed sensors, Since in field applications the number of signals to be monitored is often too large to be handled effectively by a single reconstruction model, a more viable approach is that of decomposing the problem by developing a number of reconstruction models, each one handling an individual group of signals. In this paper, Multi-Objective Genetic Algorithms (MOGAs) are devised for finding the optimal groups of signals used for building reconstruction models based on Principal Component Analysis (PCA). A weighted scheme is adopted to combine appropriately the signal predictions of the individual models. The proposed approach is applied to a real case study.
The aim of this article is to analyze and explain the results obtained when using a genetic algorithm (GA) to optimize the ascent trajectory of a conventional two-stages launcher. The purpose of this optimization is t...
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ISBN:
(纸本)9789812799463
The aim of this article is to analyze and explain the results obtained when using a genetic algorithm (GA) to optimize the ascent trajectory of a conventional two-stages launcher. The purpose of this optimization is to obtain a final stable circular Low Earth Orbit (LEO) with maximum height. A subset of parameterized variables are optimized by the GA in order to achieve the mission purpose while satisfying the constraints and maximizing the final height of the orbit, given the technical characteristics and limitations of the launcher, and a fixed payload weight. Besides, an adaptive mutation rate has been used that broadens the search space whenever a population becomes uniform, avoiding local maximums. The results have been proved to be successful and useful.
In recent years, natural and man-made disasters have been affecting increasing numbers of people throughout the world. Organisations for emergency and humanitarian aid have experienced an important growth, and efficie...
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ISBN:
(纸本)9789812799463
In recent years, natural and man-made disasters have been affecting increasing numbers of people throughout the world. Organisations for emergency and humanitarian aid have experienced an important growth, and efficiency in management becomes crucial. There is a lack of specific tools devoted to logistics of this special kind of interventions in developing countries, demanded by the organisations. A goal programming model that sustains a decision support system currently in development is presented, focusing on the transport problem to distribute humanitarian aid to the affected population of a disaster in a developing country.
Process performance can be analyzed by using process capability indices (PCIs) successfully. They are summary statistics to depict the process situation. PCIs have not reliable results if the process observations have...
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ISBN:
(纸本)9789812799463
Process performance can be analyzed by using process capability indices (PCIs) successfully. They are summary statistics to depict the process situation. PCIs have not reliable results if the process observations have correlation. In this paper, PCIs called Robust Process Capability Indices (RPCIs) are analyzed unlike traditional PCIs. Also specification limits and standard deviation are defined as fuzzy number. Fuzzy RPCIs are created for piston manufacturing process.
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