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This paper has proposed a framework in order to analyze in conditional efficient state. Proposed model can classify the objective DMU with imprecise data into following four state: (1) efficient state in any case, (2) efficient state in the condition that objective DMU has minimum input and maximum output and other DMU has any input/output levels, (3) efficient state in the condition that objective...
In this paper, we establish an effort prediction model using an artificial neural network (ANN) for complementing missing values. We add missing values to the data via collaborative filtering using the method of Tsunoda et al.'s method. In addition, we perform an evaluation experiment to compare the accuracy of the ANN model with that of the MRA model using Welch's t-test. The results show that the...
In an earlier paper, we established 9 models for estimating errors in a new project. In this paper, we integrate the 9 models into 5 by investigating similarities among the models. In addition, we establish a new model using an artificial neural network (ANN). It is becoming increasingly important for software-development corporations to ascertain how to develop software efficiently, whilst guaranteeing...
Estimating the parameters of biochemical networks from time-courses is becoming increasingly important. There have been some attempts in the past to carry out this task in an automatic way. In this research, SASS, a novel heuristic optimisation algorithm that has only one control parameter, has been used to solve this problem. While the obtained estimations are similar to those using other recent...
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