This paper focuses on personalized information retrieval which is a research focus in Web Information Service,and it's the key technology of enhance retrieval quality. As a user concept map composed of some concep...
详细信息
This work discusses usage of Lindenmayer's grammar for finding the optimum usage of a land. First, we discuss adaptation of land's value theory and Lindenmayer's grammar. Next are discussed the present att...
详细信息
This work discusses usage of Lindenmayer's grammar for finding the optimum usage of a land. First, we discuss adaptation of land's value theory and Lindenmayer's grammar. Next are discussed the present attempts to make a computer program. Then the paper discusses future developments to the system.
Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications,such as climate ***,spatial adaptation is achieved by eleme...
详细信息
Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications,such as climate ***,spatial adaptation is achieved by element subdivision (h adaptation) with a primary goal of resolving the local length scales of interest.A sec- ond,less-popular method of spatial adaptivity is called'mesh motion'(r adaptation); the smooth repositioning of mesh node points aimed at resizing existing elements to capture the local length *** paper proposes an adaptation method based on a combination of both element subdivision and node point repositioning (rh adaptation). By combining these two methods using the notion of a mobility function,the proposed approach seeks to increase the flexibility and extensibility of mesh motion algorithms while providing a somewhat smoother transition between refined regions than is pro- duced by element subdivision ***,in an attempt to support the requirements of a very general class of climate simulation applications,the proposed method is de- signed to accommodate unstructured,polygonal mesh topologies in addition to the most popular mesh types.
In this study six different mode switching techniques (i.e. timeout mode switching, non-preferred hand mode switching, barrel button mode switching, pressure mode switching, tilt mode switching and azimuth mode switch...
详细信息
ISBN:
(纸本)9780769534718
In this study six different mode switching techniques (i.e. timeout mode switching, non-preferred hand mode switching, barrel button mode switching, pressure mode switching, tilt mode switching and azimuth mode switching) based on multiple parameters pen input are proposed. The results indicate that the techniques utilizing tilt angle and azimuth offer faster performance than the others.
The main objective of this work is to automatically design neural network models with sigmoidal basis units for classification tasks, so that classifiers are obtained in the most balanced way possible in terms of CCR ...
详细信息
We describe a novel incremental diagnostic system based on a statistical model that is trained from empirical data. The system guides the user by calculating what additional information would be most helpful for the d...
详细信息
We describe a novel incremental diagnostic system based on a statistical model that is trained from empirical data. The system guides the user by calculating what additional information would be most helpful for the diagnosis. We show that our diagnostic system can produce satisfactory classification rates, using only small amounts of available background information, such that the need of collecting vast quantities of initial training data is reduced. Further, we show that incorporation of inconsistency-checking mechanisms in our diagnostic system reduces the number of incorrect diagnoses caused by erroneous input.
Three algorithms are proposed in optimizing the regression test suite when the test suite reduction technique and test case prioritization technique are combined together. 1) Build-up algorithm, which first selects th...
详细信息
Three algorithms are proposed in optimizing the regression test suite when the test suite reduction technique and test case prioritization technique are combined together. 1) Build-up algorithm, which first selects the essential test case and then the one with the biggest additional contribution until all the requirements are satisfied. 2) Break-down algorithm, which iteratively discards the redundant test case with the smallest contribution until all the test cases are essential or all the requirements are satisfied. 3) Test case prioritization strategy iteratively uses build-up algorithm until all the test cases are ordered. Each test-case contribution is not only related to the importance of each requirement but also to the whole requirements set. Experimental studies are performed to show that test-suite reduction combined with the test-suite prioritization technique can provide a smaller-sized test suite with a higher ARRS value.
This paper presents a new algorithm that approximates real function evaluations using supervised learning with a surrogate method called support vector machine (SVM). We perform a comparative study among different lea...
详细信息
The main objective of this work is to automatically design neural network models with sigmoidal basis units for classification tasks, so that classifiers are obtained in the most balanced way possible in terms of CCR ...
详细信息
The main objective of this work is to automatically design neural network models with sigmoidal basis units for classification tasks, so that classifiers are obtained in the most balanced way possible in terms of CCR and sensitivity (given by the lowest percentage of examples correctly predicted to belong to each class). We present a memetic Pareto evolutionary NSGA2 (MPENSGA2) approach based on the Pareto-NSGAII evolution (PNSGAII) algorithm. We propose to augmente it with a local search using the improved Rprop-IRprop algorithm for the prediction of growth/no growth of L. monocytogenes as a function of the storage temperature, pH, citric (CA) and ascorbic acid (AA). The results obtained show that the generalization ability can be more efficiently improved within a framework that is multi-objective instead of a within a single-objective one.
暂无评论