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The paper is dedicated to automated and semi-automated engineering of human-machine interfaces through artificial evolution: the state-of-art, the notable problems, and the preposition of a potentially feasible evolutionary algorithm. The A/B Testing method is already widely used in web interaction design, but it utilizes a single measurable goal and therefore risks random undirected modifications...
Software development and management of large scale projects are the complicated task. To support the software developers, the object oriented methodologies are used for reducing development efforts. But still a significant amount of efforts and team work is required to design and develop the systems according to the users need. Among them the testing is a one of the key components of software development...
In this research a new android app for smartphones to smartly resize images is presented. The smart image resize method was based on a dynamic programming approach that used image edge tangent flow as the energy function to be minimized, known as flow-guided seam carving method. However, a simple but useful interface is needed in a mobile app. Therefore, we developed an interactive approach to image...
The placing components and routing are very important in designing PCB, although they require a lot of time and precision. Auto placer and auto router application that are available so far are proprietary and thus cannot be developed freely. This research proposes optimization design of PCB alongside with genetic algorithm and routing lee algorithm. The genetic algorithm allocates components automatically...
Oral carcinogenesis, a multistep phenomenon often precedes by oral pre-cancers like leukoplakia (OLK). Differentially expressed (DE) gene analysis of microarray data followed by functional classification provides an idea of alteration of biological functions associated with disease progression. In this context, microRNA (miRNA) microarray data analysis for functional classification is still a challenge,...
This paper presents a non-linear, data driven Adaptive Network based Fuzzy Inference System (ANFIS) modeling of a Two Tanks Hydraulic System (TTHS). The paper also addresses the design of a Type 1 Fuzzy Logic Controller optimized with Genetic Algorithms (GA). The controller was designed and tested in simulation with the obtained ANFIS model and validated in real-time with the actual TTHS. Obtained...
In order to solve the problems of test message being rejected by the network server running the network protocol, a novel method is proposed by introducing the genetic algorithm into the test message generation process. Firstly, under the calculation of distance matrix, alignment of protocol sequence and identification of packet format are accomplished. Secondly, the genetic algorithm is introduced,...
A method of feature selection using elitist Genetic Algorithm is proposed in this work. Stratified-tenfold-cross-validation classification accuracy is used as fitness function. The method developed can detect redundant and irrelevant features, consequently producing the optimal feature set. The algorithm is carried out on the four benchmark datasets. Results of the experiments carried out shows that...
Autonomous vehicles have many practical applications, but the development of software controllers for such use has several difficulties. This work presents a finite state-machine model with evolved parameters as a suitable solution for a self-driving car, an approach that enables a clear division of behaviors in states, providing an easy way to test different configurations and simplifying the search...
Various methods have been utilized for the cooperative tasking of unmanned aerial vehicles (UAVs), with the genetic algorithm (GA) being a technique that has proven to be versatile and effective for this use. The design and implementation of a GA is both an art and a science that brings together creativity, theoretical foundations and engineering. The focus of this paper is to show how the fitness...
Exhaustive testing is extremely difficult to perform owing to the large number of combinations. Thus, sampling and finding the optimal test suite from a set of feasible test cases becomes a central concern. Addressing this issue, the adoption of t-way testing (where t indicates the interaction strength) has come into the limelight. In order to summarize the achievements so far and facilitate future...
A Deep Neural Network (DNN) using the same activation function for all hidden neurons has an optimization limitation due to its single mathematical functionality. To solve it, a new DNN with different activation functions is designed to globally optimize both parameters (weights and biases) and function selections. In addition, a novel Genetic Deep Neural Network (GDNN) with different activation functions...
Software testing is an essential part of the SDLC(Software Development Life Cycle). Test scenarios are used to derive test cases for model based testing. However, with the software rapidly growing in size and complexity, the cost of software will be too high if we want to test all the test cases. So this paper presents an approach using Hybrid Genetic Algorithm(HGA) to prioritize test scenarios, which...
A class that provides a fat interface violates the interface segregation principle, which states that the clients of the class should not be coupled with methods that they do not need. Coping with this problem involves extracting interfaces that satisfy the needs of the clients. In this paper, we envision an interface extraction method that serves a combination of four principles: (1) fitness, as...
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...
In this study, seismic attributes have been used to estimate well logs in one of the Iranian petroleum reservoirs. Three static methods have been evaluated: the linear model, the multilayer perceptron (MLP) and the radial basis function (RBF). For linear case, the selection of appropriate attributes was determined by forward selection and for nonlinear one, the selection was based on the genetic algorithm...
In this paper, Ant Lion Optimizer (ALO) was presented to train Multi-Layer Perceptron (MLP). ALO was used to find the weights and biases of the MLP to achieve a minimum error and a high classification rate. Four standard classification datasets were used to benchmark the performance of the proposed method. In addition, the performance of the proposed method were compared with three well-known optimization...
Pairwise testing is an effective combinatorial test generation technique that can generate relative small test suite to cover all pairs of parameter values at least once. Genetic algorithm has been used for pairwise test suite generation by some researchers. In order to improve the performance of genetic algorithm, this paper proposes a hybrid optimization algorithm by augmenting genetic algorithm...
Effective testing is essential for assuring software quality. While regression testing is time-consuming, the fault detection capability may be compromised if some test cases are discarded. Test case prioritization is a viable solution. To the best of our knowledge, the most effective test case prioritization approach is still the additional greedy algorithm, and existing search-based algorithms have...
The purposes of this research are to find a model to forecast the electricity consumption in a household based on fuzzy cognitive map (FCM) prediction capabilities. The data analysis has been performed with three different learning algorithms based on the fuzzy cognitive map model which are (a) the multi-step gradient method (MGM), (b) the real coded genetic algorithm (RCGA) and (c) the structure...
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