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In the testing Cloud platform, there exist too many testing tasks waiting for scheduling at the same time. How to design scheduling strategy is really a challenging problem. In this paper, we firstly analyze the relationship between the testing tasks and establish the task relationship model. Based on these analyses, we propose a dynamic task scheduling strategy using genetic algorithm, which not...
There is an increasing research interest in unmanned autonomous vehicles (UAVs) such as quadrotors. These researches applies these quadrotors for much more complicated tasks with most requiring cameras and GPS modules for positioning. This paper presents an alternative way of position localization of a quadrotor without the use of cameras and GPS modules by means of transceivers and Genetic Algorithm...
The rapidly growing amount of data being produced in the world has become a challenging problem for decision support systems. These data are located in disparate sites while time, cost and privacy concerns makes it impossible to aggregate them into one location. Information fusion systems aim to make decisions by getting the outputs of the distributed sources. Since each source is making its local...
A Markov Chain approach to estimate reliability of a software system using genetic algorithm is presented. In this approach, the code is initially converted into control flow graph and then reduced to a dd-graph. The fitness function of the genetic algorithm is calculated based on the path coverage. The edges of the dd-graph are assigned weights based on the Markov transition probability matrix and...
Regression Testing is an inevitable and very costly maintenance activity that is implemented to make sure the validity of modified software in a time and resource constrained environment. Execution of entire test suite is not possible so it is necessary to apply techniques like Test Case Selection and Test Case Prioritization to select and prioritize a minimum set of test cases, fulfilling some chosen...
Comparing with the traditional method of credit evaluation, this paper presents a classification evaluation method based on the projection pursuit and the fuzzy rules. Firstly, we use projection pursuit technology to reducing the dimensionality of the training sample, and use genetic algorithm to optimize the projection direction to find the best projection value, classification in accordance with...
Due to the strong global optimization capability and fast convergence, PSO has shown its efficiency in solving various real world benchmark applications. But premature convergence is one of the major drawback of PSO. In this paper to address this issue, a hybrid PSO-GA based Pi-sigma neural network with standard back propagation gradient descent learning (PSO-GA-PSNN) has been proposed for classification...
Test scheduling is an important issue for testing the SoC (system-on-chip). This work uses a parallel elite genetic algorithm for test scheduling to reduce the test application time under the peak power constraint. It is applied to the 2D SoC and experimental results on benchmark circuits show that it is one of the most effective algorithms in solving the problem.
Condition monitoring and fault diagnosis of rotating machinery are very significant and practically challenging fields in industries for reducing maintenance costs. Fault diagnosis may be interpreted as a classification problem; therefore artificial intelligence-based classifiers can be efficiently used to classify normal and faulty machine conditions. K-means clustering is one of the methods applied...
Hybridization has become one of the current focuses of new research areas of the evolutionary algorithms over the past few years. Hybridization offers better speed of convergence to the evolutionary approach and better accuracy of the final solutions. This paper presents a hybrid non-dominated sorting genetic algorithm-II (NSGA-II) to optimize Three-Term Backpropagation (TBP) network in terms of two...
The weather changes easily these days, that is difficult to predict. Yet, weather forecasting is the important and useful thing in all aspects of life for instance, in the agriculture field to decide the time of planting. Thus, weather forecast of rain fall intensity particularly in region of Kemayoran Jakarta is conducted in this research. The forecast system built uses Hybrid Genetic Algorithm (GA)...
Prediction time series of economic indicator optimized by Algorithm Genetic (AG) is able in getting best individual with the accuracy around 97%. The parameter of AG are maximum population is 100; Ra are 5 and 10, while Rb are −5 and −10; probability mutation (Pmut) is 0.3; and probability crossover (Pc) is 0.9. It was caused by AG had longer opportunity in fitting data using scenario data from 1961...
The classification performance of Support Vector Machine (SVM) is heavily influenced by its kernel parameter g and penalty factor c. in this paper, Cross-validation (CV) based grid-search optimization, CV-based genetic algorithm (GA) and CV-based particle swarm optimization (PSO) are respectively used for parameters optimization in SVM for fault classification of inverters in traction converter. Simulation...
A new method is presented to detect catastrophic defects from the signal analysis of dynamic current consumption waveforms of analog circuits. While other techniques use the whole information in a Root-Mean-Square computation or in black-box techniques such as a neural network, the central point of this work resides in the selection of waveform samples to create a signature able to discriminate a...
This paper proposes a genetic algorithm (GA)method to generate test scenarios for testing proper fail-safe behavior for web applications. Unlike other approaches which combine fault trees with state charts, we create mitigation tests from an existing functional black box test suite. A genetic algorithm is used that determines points of failures and type of failure that need to be tested. Mitigation...
In software development, the most time consuming phase is maintenance. Regression testing, which is a part of maintenance, deals with test case prioritization that aims to increase rate of fault detection with less number of tests. In our study, we used 100 tests and 1000 faults; however, faults are detected by tests using genetic algorithm and improved genetic algorithm. After test case prioritization,...
In this paper, we propose a Binary Coded Genetic Algorithm with Ensemble Classification feature selection procedure designed for steganalysis. Proposed feature selection method was used for searching the most appropriate subset of features from 22510 dimension feature space superior for JPEG steganal-ysis. Reduced set of features shows better classification accuracy for JPEG steganalysis compared...
Software testing is one of the important stages of software development. In software development, developers always depend on testing to reveal bugs. In the maintenance stage test suite size grow because of integration of new technique. Addition of new technique force to create new test case which increase the size of test suite. In regression testing new test case may be added to the test suite during...
The availability of automated tool support is an important consideration for software developers before they can incorporate higher order mutation testing into their software development processes. This paper presents HOMAJ, a higher order mutation testing tool for AspectJ and Java. HOMAJ automates the process of generating and evaluating first order mutants (FOMs) and higher order mutants (HOMs)...
Genetic Algorithms are heuristic approach for forming the bases of search based algorithms. It applies the mechanism of the natural selection of genes & the phenomena's associated with the genetics like mutation, crossover, and replication to provide solutions in some complex searches. In this paper, we have reviewed their applications in context of the Object oriented paradigm thus proving their...
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