Swathypriyadharsini P^1,∗, K.Premalatha^2,†

Computer Systems Science and Engineering, Vol.35, No.1, pp. 39-50, 2020, DOI:10.32604/csse.2020.35.039

Abstract Microarrays have reformed biotechnological research in the past decade. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks with larger volume of genes also increases the challenges of comprehending and interpretation of the resulting mass of data. Clustering addresses these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent… More >

Sa’ed Abed^∗, Mohammed H. Ali^†, Mohammad Al-Shayeji^‡

Computer Systems Science and Engineering, Vol.35, No.1, pp. 21-37, 2020, DOI:10.32604/csse.2020.35.021

Abstract Today, there is a growing demand for computer vision and image processing in different areas and applications such as military surveillance, and biological and medical imaging. Edge detection is a vital image processing technique used as a pre-processing step in many computer vision algorithms. However, the presence of noise makes the edge detection task more challenging; therefore, an image restoration technique is needed to tackle this obstacle by presenting an adaptive solution. As the complexity of processing is rising due to recent high-definition technologies, the expanse of data attained by the image is increasing dramatically.… More >

Ridvan Saraçoğlu^*, Ahmet Fatih Kazankaya^†

Computer Systems Science and Engineering, Vol.35, No.1, pp. 13-19, 2020, DOI:10.32604/csse.2020.35.013

Abstract The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a More >

David Corral-Plaza¹, Juan Boubeta-Puig¹, Guadalupe Ortiz¹, Alfonso Garcia-de-Prado^2,*

Computer Systems Science and Engineering, Vol.35, No.1, pp. 5-12, 2020, DOI:10.32604/csse.2020.35.005

Abstract Air pollution is currently receiving more attention by international governments and organizations. Nevertheless, current systems for air quality monitoring lack essential requirements which are key in order to be effective concerning users’ access to the information and efficient regarding real-time monitoring and notification. This paper presents an Internet of Things platform for air station remote sensing and smart monitoring that combines Big Data and Cloud Computing paradigms to process and correlate air pollutant concentrations coming from multiple remote stations, as well as to trigger automatic and personalized alerts when a health risk for their particular More >

Zhenhua Guo^1,2, Lixin Zhang^1,*, Xue Hu¹, Huanmei Chen²

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 625-630, 2020, DOI:10.32604/iasc.2020.013941

Abstract Wind speed prediction is an important part of the wind farm management and wind power grid connection. Having accurate prediction of short-term wind speed is the basis for predicting wind power. This paper proposes a short-term wind speed prediction strategy based on the wavelet analysis and the multilayer perceptual neural network for the Dabancheng area, in China. Four wavelet neural network models using the Morlet function as the wavelet basis function were developed to forecast short-term wind speed in January, April, July, and October. Predicted wind speed was compared across the four models using the More >

Fanxiu Dong^*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 617-624, 2020, DOI:10.32604/iasc.2020.013940

Abstract At present, the allocation of the medical service resources is directed at a single service resource, and there are many unreasonable problems, which causes medical cost to be high. Based on this, the application of the DRGs and the fuzzy demand in the medical service resource allocation based on the data mining algorithm is proposed. The application research of the DRGs and the data mining algorithm is simply analyzed, then the uncertain demand estimation is applied to the fuzzy demand processing based on the fuzzy demand theory and the medical service resources are configured under More >

Hao Peng^*, Qiao Li

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 609-616, 2020, DOI:10.32604/iasc.2020.013939

Abstract This paper represents a neural network model for the Web page information extraction based on the depth learning technology, and implements the model algorithm using the TensorFlow system. We then complete a detailed experimental analysis of the information extraction effect of Web pages on the same website, then show statistics on the accuracy index of the page information extraction, and optimize some parameters in the model according to the experimental results. On the premise of achieving ideal experimental results, an algorithm for migrating the model to the same pages of other websites for information extraction… More >

Meng Wei^*, Ningxin Zhang, Yuan Tong, Yu Song

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 597-607, 2020, DOI:10.32604/iasc.2020.013938

Abstract The traditional radar signal detection mode of the analog digital converter (ADC) has a low prediction efficiency. Therefore, the advanced prediction model of the tunnel geological radar based on the cluster computing was designed. The completeness factor of the detection radar signal was calculated by the computer cluster effect, and then the information extraction and information integration of the radar pulse for the radar detection signal was determined. Moreover, the multi-order nonlinear regression forecasting model restructured the received signal. Thus, the prediction of the radar detection signal was achieved. In order to ensure the effectiveness More >

Shaoyun Long^1,*, Qianying Long²

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 585-595, 2020, DOI:10.32604/iasc.2020.013937

Abstract The traditional factor analysis models, such as the generalized linear regression model and the gistic regression model have disadvantages of large standard error of analysis results. For this purpose, a multilevel factor analysis model based on time series and independent variable data is designed. The OLS estimation analysis method is used to establish the basic environment form, to derive the model calculation parameters and to complete the environment construction of the multilevel analysis model. On the basis of the construction environment, the double-level environment reference module and the multilevel factor analysis module are designed to More >

Linlin Zhang^*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 577-583, 2020, DOI:10.32604/iasc.2020.013936

Abstract The change of entrepreneurial social relations will have a negative impact on the enterprise performance. There is a significant positive correlation between the change of entrepreneurs' social relations and the negative impact of corporate performance. In order to reduce the negative impact of the social relationship of entrepreneurs and improve the profitability of the enterprises, a communication model of the entrepreneur social relationship change and the negative influence of the enterprise performance is proposed based on the closeness decision. The communication model of the negative impact of the enterprise performance and the enterprise performance are… More >