Search results1 – 3 of 3
Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data. An important issue on data integration…
Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data. An important issue on data integration is the existence of conflicts among the different data sources. Data sources may conflict with each other at data level, which is defined as data inconsistency. The purpose of this paper is to aim at this problem and propose a solution for data inconsistency in data integration.
A relational data model extended with data source quality criteria is first defined. Then based on the proposed data model, a data inconsistency solution strategy is provided. To accomplish the strategy, fuzzy multi-attribute decision-making (MADM) approach based on data source quality criteria is applied to obtain the results. Finally, users feedbacks strategies are proposed to optimize the result of fuzzy MADM approach as the final data inconsistent solution.
To evaluate the proposed method, the data obtained from the sensors are extracted. Some experiments are designed and performed to explain the effectiveness of the proposed strategy. The results substantiate that the solution has a better performance than the other methods on correctness, time cost and stability indicators.
Since the inconsistent data collected from the sensors are pervasive, the proposed method can solve this problem and correct the wrong choice to some extent.
In this paper, for the first time the authors study the effect of users feedbacks on integration results aiming at the inconsistent data.
The two main purposes of this paper are: first, the development of a new optimization algorithm called GHSACO by incorporating the global-best harmony search (GHS) which…
The two main purposes of this paper are: first, the development of a new optimization algorithm called GHSACO by incorporating the global-best harmony search (GHS) which is a stochastic optimization algorithm recently developed, with the ant colony optimization (ACO) algorithm. Second, design of a new indirect adaptive recurrent fuzzy-neural controller (IARFNNC) for uncertain nonlinear systems using the developed optimization method (GHSACO) and the concept of the supervisory controller.
The novel optimization method introduces a novel improvization process, which is different from that of the GHS in the following aspects: a modified harmony memory representation and conception. The use of a global random switching mechanism to monitor the choice between the ACO and GHS. An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The developed optimization method is applied for parametric optimization of all recurrent fuzzy neural networks adaptive controller parameters. In addition, in order to guarantee that the system states are confined to the safe region, a supervisory controller is incorporated into the IARFNNC global structure.
First, to analyze the performance of GHSACO method and shows its effectiveness, some benchmark functions with different dimensions are used. Simulation results demonstrate that it can find significantly better solutions when compared with the Harmony Search (HS), GHS, improved HS (IHS) and conventional ACO algorithm. In addition, simulation results obtained using an example of nonlinear system shows clearly the feasibility and the applicability of the proposed control method and the superiority of the GHSACO method compared to the HS, its variants, particle swarm optimization, and genetic algorithms applied to the same problem.
The proposed new GHS algorithm is more efficient than the original HS method and its most known variants IHS and GHS. The proposed control method is applicable to any uncertain nonlinear system belongs in the class of systems treated in this paper.
From the sixteenth to eighteenth century, China underwent a commercial revolution similar to the one in contemporaneous Europe. The rise of market did foster the rise of a…
From the sixteenth to eighteenth century, China underwent a commercial revolution similar to the one in contemporaneous Europe. The rise of market did foster the rise of a nascent bourgeois and the concomitant rise of a liberal, populist version of Confucianism, which advocated a more decentralized and less authoritarian political system in the last few decades of the Ming dynasty (1368–1644). But after the collapse of the Ming Empire and the establishment of the Qing Empire (1644–1911) by the Manchu conquerors, the new rulers designated the late-Ming liberal ideologies as heretics, and they resurrected the most conservative form of Confucianism as the political orthodoxy. Under the principle of filial piety given by this orthodoxy, the whole empire was imagined as a fictitious family with the emperor as the grand patriarch and the civil bureaucrats and subjects as children or grandchildren. Under the highly centralized administrative and communicative apparatus of the Qing state, this ideology of the fictitious patrimonial state penetrated into the lowest level of the society. The subsequent paternalist, authoritarian, and moralizing politics of the Qing state contributed to China’s nontransition to capitalism despite its advanced market economy, and helped explain the peculiar form and trajectory of China’s popular contention in the eighteenth century. I also argue that this tradition of fictitious patrimonial politics continued to shape the state-making processes in twentieth-century China and beyond.