The present paper deals with control of system consists surge tank, pump a and pipeline. Model of this system is based on hydro-electrical analogy. For purpose of control it is designed a regulator with estimator. Reg...
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Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other *** Imbalanced distribution of data is a natural occu...
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Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other *** Imbalanced distribution of data is a natural occurrence in real world datasets,so needed to be dealt with carefully to get important *** case of imbalance in data sets,traditional classifiers have to sacrifice their performances,therefore lead to *** paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this *** have adapted the‘existing algorithm modification solution’to learn from imbalanced datasets that classify data without manipulating the natural distribution of data unlike the other popular data balancing *** K nearest neighbor is a non-parametric classification method that is mostly used in machine learning *** classification with the nearest neighbor clears the belonging of an instance to classes and optimal weights with improved nearest neighbor concept helping to correctly classify imbalanced *** proposed hybrid approach takes care of imbalance nature of data and reduces the inaccuracies appear in applications of original and traditional *** show that it performs well over the existing fuzzy nearest neighbor and weighted neighbor strategies for imbalanced learning.
Open and dynamic environments lead to inher- ent uncertainty of Web service QoS (Quality of Service), and the QoS-aware service selection problem can be looked upon as a decision problem under uncertainty. We use an...
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Open and dynamic environments lead to inher- ent uncertainty of Web service QoS (Quality of Service), and the QoS-aware service selection problem can be looked upon as a decision problem under uncertainty. We use an empiri- cal distribution function to describe the uncertainty of scores obtained from historical transactions. We then propose an approach to discovering the admissible set of services in- cluding alternative services that are not dominated by any other alternatives according to the expected utility criterion. Stochastic dominance (SD) rules are used to compare two services with uncertain scores regardless of the distribution form of their uncertain scores. By using the properties of SD rules, an algorithm is developed to reduce the number of SD tests, by which the admissible services can be reported pro- gressively. We prove that the proposed algorithm can be run on partitioned or incremental alternative services. Moreover, we achieve some useful theoretical conclusions for correct pruning of unnecessary calculations and comparisons in each SD test, by which the efficiency of the SD tests can be im- proved. We make a comprehensive experimental study using real datasets to evaluate the effectiveness, efficiency, and scal- ability of the proposed algorithm.
This study proposes a technique for automated detection and diagnosis of stroke lesions based on diffusion-weighted imaging (DWI). The technique consists of several stages which are pre-processing, segmentation, featu...
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ISBN:
(纸本)9789881404732
This study proposes a technique for automated detection and diagnosis of stroke lesions based on diffusion-weighted imaging (DWI). The technique consists of several stages which are pre-processing, segmentation, feature extraction, and classification. The proposed analytical framework of this study is based on Fuzzy C-Means (FCM) segmentation, statistical parameters for features extraction and rule-based classification. The three-dimensional (3D) view is developed to enable observing directions of the gained 3D structure along the three axes. The segmentation results have been validated by using Jaccard and Dice indices, false positive rate (FPR), and false negative rate (FNR). The results for Jaccard, Dice, FPR and FNR of acute stroke are 0.7, 0.84, 0.049 and 0.205, respectively. The accuracy for acute stroke is 90% and chronic stroke is 70%, while the sensitivity and the specificity is 84.38% and 83.33%, respectively.
This paper investigates the problem of yaw moment control of humanoid robot and presents a robust adaptive control system for compensating the undesired yaw moment. In order to get the ideal ankle joint trajectory wit...
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ISBN:
(纸本)9781467374439
This paper investigates the problem of yaw moment control of humanoid robot and presents a robust adaptive control system for compensating the undesired yaw moment. In order to get the ideal ankle joint trajectory with low energy consumption,a novel yaw moment control based on ankle is proposed. The main strategy in this method is to adjust ankle joint trajectory in a way to exert a moment for counteracting the factors which generate the undesired yaw moment. Given the optimized ankle joint angles motion, an adaptive fuzzy control system is proposed to track the desired trajectories with model uncertainties and the stability proof is provided. Simulation results validate the proposed method.
To electric furnace's characters as non-linear and time-varying, we designed a fuzzy PID controller, and made some simulation through MATLAB, at the same time we used a traditional PID controller and simulated, th...
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As described by digital system the language Verilog HDL is widely used in the circuit design, its own advantages to be able to use software language describe hardware features that makes it has good readability, porta...
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We extend a 'surrogate problem' approach that is developed for a class of stochastic discrete optimization problems so as to tackle the global signal settings and traffic assignment combined problem. We compar...
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Bio-modeling has important role in virtual reality in telemedicine providing base for simulations and decisions. Virtual reality is based on sequences of volumetric images whose motion is captured in time. These data ...
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ISBN:
(纸本)9789973879141
Bio-modeling has important role in virtual reality in telemedicine providing base for simulations and decisions. Virtual reality is based on sequences of volumetric images whose motion is captured in time. These data sets are typically very large in size and demand a great amount of resources for storage and transmission. Therefore it is necessary to compress this data both fast and efficiently. We will propose combination of lossless and lossy compression models to obtain toset demands.
In this article, a Lyapunov-based control concept is presented combining variable structure and adaptive control. The considered system class comprises single-input systems which are affected by structured and unstruc...
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