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  • Open Access

    ARTICLE

    Fuzzy Based MPPT and Solar Power Forecasting Using Artificial Intelligence

    G. Geethamahalakshmi1,*, N. Kalaiarasi2, D. Nageswari1

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1667-1685, 2022, DOI:10.32604/iasc.2022.022728

    Abstract Solar energy is the radiant heat and light energy harvested by ultra violet rays to convert into electrical Direct Current (DC). The solar energy stood ahead of other renewable energy as it can produce a constant level of alternating current over the year with minimal harmonic distortions. The renewable energy attracts the energy harvesters as there is rise of deficiency of carbon and reduction of efficiency in thermal energy generation. The concerns associated with the solar power generation are the fluctuation in the generated direct current due to the displacement of sun and deviation in the quantity of solar rays… More >

  • Open Access

    ARTICLE

    Fast Access and Retrieval of Big Data Based on Unique Identification

    Wenshun Sheng1,*, Aiping Xu2, Shengli Wu3

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1781-1795, 2022, DOI:10.32604/iasc.2022.022571

    Abstract In big data applications, the data are usually stored in data files, whose data file structures, field structures, data types and lengths are not uniform. Therefore, if these data are stored in the traditional relational database, it is difficult to meet the requirements of fast storage and access. To solve this problem, we propose the mapping model between the source data file and the target HBase file. Our method solves the heterogeneity of the file object and the universality of the storage conversion. Firstly, based on the mapping model, we design “RowKey”, generation rules and algorithm. Then according to the… More >

  • Open Access

    ARTICLE

    Covid-19 Symptoms Periods Detection Using Transfer-Learning Techniques

    Fahad Albogamy1, Mohammed Faisal2,3,*, Mohammed Arafah4, Hebah ElGibreen3,5

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1921-1937, 2022, DOI:10.32604/iasc.2022.022559

    Abstract The inflationary illness caused by extreme acute respiratory syndrome coronavirus in 2019 (COVID-19) is an infectious and deadly disease. COVID-19 was first found in Wuhan, China, in December 2019, and has since spread worldwide. Globally, there have been more than 198 M cases and over 4.22 M deaths, as of the first of Augest, 2021. Therefore, an automated and fast diagnosis system needs to be introduced as a simple, alternative diagnosis choice to avoid the spread of COVID-19. The main contributions of this research are 1) the COVID-19 Period Detection System (CPDS), that used to detect the symptoms periods or… More >

  • Open Access

    ARTICLE

    Soil Urea Analysis Using Mid-Infrared Spectroscopy and Machine Learning

    J. Haritha1,*, R. S. Valarmathi2, M. Kalamani3

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1867-1880, 2022, DOI:10.32604/iasc.2022.022547

    Abstract Urea is the most common fertilizer used by the farmers. In this study, the variation of mid-infrared transmittance spectra with addition of urea in soil was studied for five different concentrations of urea. 150 gm of soil is taken and dried in a hot air oven for 5 h at 80°C and then samples are prepared by adding urea and water to it. The spectral signature of soil with urea is obtained by using an Infrared Spectrometer that reads the spectra in the mid infra-red region. The analysis is done using Partial Least Square Regression and Support Vector Machine algorithms… More >

  • Open Access

    ARTICLE

    Virtualized Load Balancer for Hybrid Cloud Using Genetic Algorithm

    S. Manikandan1,*, M. Chinnadurai2

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1459-1466, 2022, DOI:10.32604/iasc.2022.022527

    Abstract Load Balancing is an important factor handling resource during running and execution time in real time applications. Virtual machines are used for dynamically access and share the resources. As per current scenario cloud computing is played major for storage, resource accessing, resource pooling and internet based service offering. Usage of cloud computing services is dynamically increased such as online shopping, education, ticketing, etc. Many users can use the cloud resources and load balancing is used for adjusting the virtual machine and balance the node. Our proposed virtualized genetic algorithms are to provide balanced virtual machine services in Hybrid cloud. The… More >

  • Open Access

    ARTICLE

    Aquarium Monitoring System Based on Internet of Things

    Wen-Tsai Sung1, Shuo-Chen Tasi1, Sung-Jung Hsiao2,*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1649-1666, 2022, DOI:10.32604/iasc.2022.022501

    Abstract With the ever-increasing richness of social resources, the number of devices using the Internet of Things is also increasing. Currently, many people keep pets such as fish in their homes, and they need to be carefully taken care of. In particular, it is necessary to create a safe and comfortable environment for them and to maintain this environment continuously. An adverse environment can affect the growth of fish and may even result in their death. This study used the LinkIt 7697 module and the BlocklyDuino editor to produce a control system for a smart aquarium. The purpose of this system… More >

  • Open Access

    ARTICLE

    Hybrid Deep Learning Framework for Privacy Preservation in Geo-Distributed Data Centre

    S. Nithyanantham1,*, G. Singaravel2

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1905-1919, 2022, DOI:10.32604/iasc.2022.022499

    Abstract In recent times, a huge amount of data is being created from different sources and the size of the data generated on the Internet has already surpassed two Exabytes. Big Data processing and analysis can be employed in many disciplines which can aid the decision-making process with privacy preservation of users’ private data. To store large quantity of data, Geo-Distributed Data Centres (GDDC) are developed. In recent times, several applications comprising data analytics and machine learning have been designed for GDDC. In this view, this paper presents a hybrid deep learning framework for privacy preservation in distributed DCs. The proposed… More >

  • Open Access

    ARTICLE

    Fair and Stable Matching Virtual Machine Resource Allocation Method

    Liang Dai1, AoSong He1, Guang Sun1,3, Yuxing Pan2,*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1831-1842, 2022, DOI:10.32604/iasc.2022.022438

    Abstract In order to unify the management and scheduling of cloud resources, cloud platforms use virtualization technology to re-integrate multiple computing resources in the cloud and build virtual units on physical machines to achieve dynamic provisioning of resources by configuring virtual units of various sizes. Therefore, how to reasonably determine the mapping relationship between virtual units and physical machines is an important research topic for cloud resource scheduling. In this paper, we propose a fair cloud virtual machine resource allocation method of using the stable matching theory. Our allocation method considers the allocation of resources from both user’s demand and cloud… More >

  • Open Access

    ARTICLE

    Handling High Dimensionality in Ensemble Learning for Arrhythmia Prediction

    Fuad Ali Mohammed Al-Yarimi*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1729-1742, 2022, DOI:10.32604/iasc.2022.022418

    Abstract Computer-aided arrhythmia prediction from ECG (electrocardiograms) is essential in clinical practices, which promises to reduce the mortality caused by inexperienced clinical practitioners. Moreover, computer-aided methods often succeed in the early detection of arrhythmia scope from electrocardiogram reports. Machine learning is the buzz of computer-aided clinical practices. Particularly, computer-aided arrhythmia prediction methods highly adopted machine learning methods. However, the high dimensionality in feature values considered for the machine learning models’ training phase often causes false alarming. This manuscript addressed the high dimensionality in the learning phase and proposed an (Ensemble Learning method for Arrhythmia Prediction) ELAP (ensemble learning-based arrhythmia prediction). The… More >

  • Open Access

    ARTICLE

    An Innovative Approach for Water Distribution Systems

    Van-Phuong Ta*, Dinh-Nhon Truong, Nguyen-Thanh Nhan

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1605-1615, 2022, DOI:10.32604/iasc.2022.022374

    Abstract Water Distribution System (WDS) is one of the important phases of the Water Treatment Plant (WTP) and plays a crucial role in plant, animal, and human life. The WDS aims not only to supply a continuous, stable water amount but also to reduce energy consumption as little as possible during operation. To keep the continuous, stable water amount, the water pressure in the pipe network of the WDS must be maintained at desired set points under the effecting of uncertainties, disturbances, and noises. For saving the energy requirement, a Variable Frequency Driver (VFD) was utilized to control the speed of… More >

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