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  • Open Access

    ARTICLE

    Inferential Statistics and Machine Learning Models for Short-Term Wind Power Forecasting

    Ming Zhang, Hongbo Li, Xing Deng*

    Energy Engineering, Vol.119, No.1, pp. 237-252, 2022, DOI:10.32604/EE.2022.017916 - 22 November 2021

    Abstract The inherent randomness, intermittence and volatility of wind power generation compromise the quality of the wind power system, resulting in uncertainty in the system's optimal scheduling. As a result, it's critical to improve power quality and assure real-time power grid scheduling and grid-connected wind farm operation. Inferred statistics are utilized in this research to infer general features based on the selected information, confirming that there are differences between two forecasting categories: Forecast Category 1 (0–11 h ahead) and Forecast Category 2 (12–23 h ahead). In z-tests, the null hypothesis provides the corresponding quantitative findings. To More >

  • Open Access

    ARTICLE

    A Secure Encrypted Classified Electronic Healthcare Data for Public Cloud Environment

    Kirupa Shankar Komathi Maathavan1,*, Santhi Venkatraman2

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 765-779, 2022, DOI:10.32604/iasc.2022.022276 - 17 November 2021

    Abstract The major operation of the blood bank supply chain is to estimate the demand, perform inventory management and distribute adequate blood for the needs. The proliferation of big data in the blood bank supply chain and data management needs an intelligent, automated system to classify the essential data so that the requests can be handled easily with less human intervention. Big data in the blood bank domain refers to the collection, organization, and analysis of large volumes of data to obtain useful information. For this purpose, in this research work we have employed machine learning… More >

  • Open Access

    ARTICLE

    Quality Prediction of Wearable Apps in the Google Play Store

    Shifa Siddiqui1, Muhammad Shahzad Faisal1, Shahzada Khurram2, Azeem Irshad3, Mohammed Baz4, Habib Hamam5, Naeem Iqbal6, Muhammad Shafiq7,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 877-892, 2022, DOI:10.32604/iasc.2022.022266 - 17 November 2021

    Abstract Play Store reviews play an important role in demonstrating that decisions are made from the user’s perspective, and contain a wealth of knowledge that can be used to understand quality issues and help developers build higher-quality mobile applications. Even for very important information, it can ensure the authenticity of user-generated content. In Play Store, wearable applications were recently launched, and are always open and easy to use, and are gradually being welcomed by users. Driven by popularity and self-interest, profit-incentive developers are developing low-quality applications and hiring robots to exaggerate ratings, reviews, or install counts.… More >

  • Open Access

    ARTICLE

    From Similarities to Probabilities: Feature Engineering for Predicting Drugs’ Adverse Reactions

    Nahla H. Barakat*, Ahmed H. ElSabbagh

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1207-1224, 2022, DOI:10.32604/iasc.2022.022104 - 17 November 2021

    Abstract Social media recently became convenient platforms for different groups with common concerns to share their experiences, including Adverse Drug Reactions (ADRs). In this paper, we propose a two stage intelligent algorithm which we call “Simi_to_Prob”, that utilizes social media forums; for ranking ADRs, and evaluating the ADRs prevalence considering different age and gender groups as its first stage. In the second stage, ADRs are predicted utilizing a different data set from the Food and Drug Administration (FDA). In particular, Natural Language Processing (NLP) is used on social media to extract ranked lists of ADRs, which… More >

  • Open Access

    ARTICLE

    Classification of Parkinson Disease Based on Patient’s Voice Signal Using Machine Learning

    Imran Ahmed1, Sultan Aljahdali2, Muhammad Shakeel Khan1, Sanaa Kaddoura3,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 705-722, 2022, DOI:10.32604/iasc.2022.022037 - 17 November 2021

    Abstract Parkinson’s disease (PD) is a nervous system disorder first described as a neurological condition in 1817. It is one of the more prevalent diseases in the elderly, and Alzheimer’s is the second most common neurodegenerative illness. It impacts the patient’s movement. Symptoms start gradually with tremors, stiffness in movement, and speech and voice disorders. Researches proved that 89% of patients with Parkinson’s has speech disorder including uncertain articulation, hoarse and breathy voice and monotone pitch. The cause behind this voice change is the reduction of dopamine due to damage of neurons in the substantia nigra… More >

  • Open Access

    ARTICLE

    Machine Learning Approach for Improvement in Kitsune NID

    Abdullah Alabdulatif1, Syed Sajjad Hussain Rizvi2,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 827-840, 2022, DOI:10.32604/iasc.2022.021879 - 17 November 2021

    Abstract Network intrusion detection is the pressing need of every communication network. Many network intrusion detection systems (NIDS) have been proposed in the literature to cater to this need. In recent literature, plug-and-play NIDS, Kitsune, was proposed in 2018 and greatly appreciated in the literature. The Kitsune datasets were divided into 70% training set and 30% testing set for machine learning algorithms. Our previous study referred that the variants of the Tree algorithms such as Simple Tree, Medium Tree, Coarse Tree, RUS Boosted, and Bagged Tree have reported similar effectiveness but with slight variation inefficiency. To More >

  • Open Access

    ARTICLE

    COVID-19 Pandemic Prediction and Forecasting Using Machine Learning Classifiers

    Jabeen Sultana1,*, Anjani Kumar Singha2, Shams Tabrez Siddiqui3, Guthikonda Nagalaxmi4, Anil Kumar Sriram5, Nitish Pathak6

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1007-1024, 2022, DOI:10.32604/iasc.2022.021507 - 17 November 2021

    Abstract COVID-19 is a novel virus that spreads in multiple chains from one person to the next. When a person is infected with this virus, they experience respiratory problems as well as rise in body temperature. Heavy breathlessness is the most severe sign of this COVID-19, which can lead to serious illness in some people. However, not everyone who has been infected with this virus will experience the same symptoms. Some people develop cold and cough, while others suffer from severe headaches and fatigue. This virus freezes the entire world as each country is fighting against… More >

  • Open Access

    ARTICLE

    Defect Prediction Using Akaike and Bayesian Information Criterion

    Saleh Albahli1,*, Ghulam Nabi Ahmad Hassan Yar2

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 1117-1127, 2022, DOI:10.32604/csse.2022.021750 - 10 November 2021

    Abstract Data available in software engineering for many applications contains variability and it is not possible to say which variable helps in the process of the prediction. Most of the work present in software defect prediction is focused on the selection of best prediction techniques. For this purpose, deep learning and ensemble models have shown promising results. In contrast, there are very few researches that deals with cleaning the training data and selection of best parameter values from the data. Sometimes data available for training the models have high variability and this variability may cause a… More >

  • Open Access

    ARTICLE

    An Improved Sparrow Search Algorithm for Node Localization in WSN

    R. Thenmozhi1, Abdul Wahid Nasir2, Vijaya Krishna Sonthi3, T. Avudaiappan4, Seifedine Kadry5, Kuntha Pin6, Yunyoung Nam7,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 2037-2051, 2022, DOI:10.32604/cmc.2022.022203 - 03 November 2021

    Abstract Wireless sensor networks (WSN) comprise a set of numerous cheap sensors placed in the target region. A primary function of the WSN is to avail the location details of the event occurrences or the node. A major challenge in WSN is node localization which plays an important role in data gathering applications. Since GPS is expensive and inaccurate in indoor regions, effective node localization techniques are needed. The major intention of localization is for determining the place of node in short period with minimum computation. To achieve this, bio-inspired algorithms are used and node localization… More >

  • Open Access

    ARTICLE

    Autism Spectrum Disorder Prediction by an Explainable Deep Learning Approach

    Anupam Garg1, Anshu Parashar1, Dipto Barman2, Sahil Jain3, Divya Singhal3, Mehedi Masud4, Mohamed Abouhawwash5,6,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1459-1471, 2022, DOI:10.32604/cmc.2022.022170 - 03 November 2021

    Abstract Autism Spectrum Disorder (ASD) is a developmental disorder whose symptoms become noticeable in early years of the age though it can be present in any age group. ASD is a mental disorder which affects the communicational, social and non-verbal behaviors. It cannot be cured completely but can be reduced if detected early. An early diagnosis is hampered by the variation and severity of ASD symptoms as well as having symptoms commonly seen in other mental disorders as well. Nowadays, with the emergence of deep learning approaches in various fields, medical experts can be assisted in… More >

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