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The support vector machine (SVM) has a good generalization performance, but the classification result of the SVM in some real problems is often unsatisfied. Because SVM is sensitive to the noisy data and it may not be effective under the high level of noise. To improve the performance of SVM in the noisy environment, we propose an ensemble learning model to address the noise problem in this work....
An intelligent complementary sliding mode control (ICSMC) is proposed in this study for the fault tolerant control of a six-phase permanent magnet synchronous motor (PMSM) drive system with open phases. First, the dynamics of the six-phase PMSM drive system with a lumped uncertainty is described in detail. Then, the fault detection and operating decision method are briefly introduced. Moreover, to...
Cost estimation is an upstream activity in manufacturing and service business. Accurate cost estimation promotes profitable decision making. In this study, a cost model was developed to estimate paint cost in a spraying process of wooden toys. The required amount of paint was formerly believed as a function of only product surface area. However, data collected earlier indicated that volume and projected...
Intelligent Information Processing System has successful application in informationization of traditional industry. Exact addressing the stock case's ailment type and roots as quickly as possible has been the weight of developing information technology for veterinary. In order to assist human veterinarian expert diagnose animal ailment, this work proposes a machine diagnosing model based on KNN ailment-similarity-degree...
When collecting data to select an alternative from a finite set of alternatives that are described by multiple attributes, one must allocate effort to activities that provide information about the value of each attribute. This is a particularly relevant problem when the attribute values are estimated using experimental data. This paper discusses the problem of allocating an experimental budget amongst...
The universal multiple outlier hypothesis testing problem is studied in two settings. In the first setting, each outlier can be arbitrarily distributed, and the number of outliers is fixed and known. In the second setting, the number of outliers is unknown at the outset. Nothing is known about the typical and outlier distributions other than that they are different and have full supports. For the...
This paper proposes an online algorithm for active learning that switches between different candidate instance selection strategies (ISS) for classification in imbalanced data sets. This is important for two reasons: 1) many real-world problems have imbalanced class distributions and 2) there is no ISS that always outperforms all the other techniques. We first empirically compare the performance of...
In many network environments, a node seeks to expand the number of connections to other nodes who can make valuable transactions possible. In the possible presence of misbehaving nodes, who make harmful transactions possible, each (behaving) node must use discretion on whether to accept a prospective connection. We study this problem when the mechanism for expansion is an introduction-based reputation...
Internet company valuation has long been considered as a big challenge due to uncertainties. In this paper, a real option analysis framework is proposed to evaluate the value of Internet companies. The proposed framework consists of four steps: strategic analysis, uncertainty analysis, option identification and option analysis. Relative to traditional valuation methods, this proposed analysis framework...
Based on conditional credibility measure and conditional expected value, some properties of conditional expected value for fuzzy variables are presented, which can enrich the theoretical system of credibility theory and fuzzy processes. Inspired by the inequalities for fuzzy variables, this paper gives a several of conditional inequalities for fuzzy variables, which provide the convenience of calculating...
In this paper, a parametrical uncertainty analysis of vehicle suspension system was presented. Four degree-of-freedom(DOF) mathematical model of vehicle passive suspension has been set up and uncertainty of the model has been studied using polynomial chaos methods. By comparing with Monte Carlo simulation method, the results show that polynomial chaos methods are more efficient than Monte Carlo method...
The auxiliary company decision-making having introduced that Anshan supplies electricity mainly supports the main body of a book to apply content such as background, construction target, scheme and technology characteristic having the problem, solving systematically. But the model builds system owing to that the country electrified wire netting SG-CIM model composes in reply multi-level Cube, apply...
There is a considerable literature devoted to the field of convergence of fuzzy sequence. In this paper, a new convergence is given and the relationships between the convergence and others are proved.
Aiming at the inherent uncertain problems in motor fault diagnosis, in this paper we propose a new kind of motor fault diagnosis method, which utilize the parallel Bayesian network and D-S evidence theory based on multi-source information fusion technique. Firstly, the set of motor fault features is divided into multiple fault sub-spaces and each fault sub-space uses different parallel Bayesian network...
Although the Shapley value method can realize the fair income distribution of the R&D alliance, it cannot achieve the Pareto efficiency. We consider a R&D alliance with a supervisor as the third party in uncertain environments. When the alliance income exceeds the predetermined target income, the alliance income ought to be distributed completely among the R&D enterprises according...
Organizations use different types of information system to reach their goals. Decision makers are required to allocate a security budget and treatment strategy based on the risk priority of information systems. Each of the information systems has different components or assets. However, there is difficulty in aggregating the risk of each component. In this research a model is created to aggregate...
The Logan plot is a graphical method for reversible tracer bindings. The bias and uncertainties of this method have previously been analyzed with respect to noise, but little is known about the direct effects from varying the time sampling scheme. This study aims to investigate the effect of time sampling on the binding potential from the reference Logan plot.
Watersheds committees decisions making are usually complexes due to the need to consider many objectives and actors with different preferences. Therefore, this paper proposes a model for reducing conflicts in the watersheds committees using Strategic Choice Approach (SCA) for problem structuring and support in the decision-making process. The simulation shows that the model can be particularly useful...
Precise prediction of operating time is one of the key factors for synchronous switching to minimize the control error. In this paper an operating time prediction algorithm is proposed based on cloud model, which shows a good applicability to synchronous switching technology on HVCB equipped with hydraulic operating mechanism. The algorithm uses cloud model to build up single-condition multiple-rule...
Internet Background Radiation (IBR) traffic is a kind of abnormal traffic, which is ubiquitous on the Internet. Detecting or filtering out IBR traffic from all traffic is benefit to ensure network security. This paper proposes a novel IBR traffic filtering method based on relative uncertainty theory. It directly filters out IBR traffic from collected Net Flow data without specific configurations or...
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