A. Sheryl Oliver¹, T. Jayasankar², K. R. Sekar^3,*, T. Kalavathi Devi⁴, R. Shalini⁵, S. Poojalaxmi⁵, N. G. Viswesh⁵

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 755-770, 2021, DOI:10.32604/iasc.2021.016242 - 20 August 2021

Abstract Lung cancer is a poorly understood disease. Smokers may develop lung cancer due to the inhalation of carcinogenic substances while smoking, but non-smokers may develop this disease as well. Lung cancer can spread to other parts of the body and this process is called metastasis. Because the lung cancer is difficult to identify in the initial stages. The objective of this work is to reduce the mortality rate of the disease by identifying it at an earlier stage based on the existing symptoms. Artificial intelligence plays active roles in tasks such as entropy extraction through… More >

Amrul Faruq¹, Aminaton Marto², Shahrum Shah Abdullah^3,*

Computer Systems Science and Engineering, Vol.39, No.3, pp. 297-306, 2021, DOI:10.32604/csse.2021.017468 - 12 August 2021

Abstract The rainstorm is believed to contribute flood disasters in upstream catchments, resulting in further consequences in downstream area due to rise of river water levels. Forecasting for flood water level has been challenging, presenting complex task due to its nonlinearities and dependencies. This study proposes a support vector machine regression model, regarded as a powerful machine learning-based technique to forecast flood water levels in downstream area for different lead times. As a case study, Kelantan River in Malaysia has been selected to validate the proposed model. Four water level stations in river basin upstream were… More >

Tooba Batool¹, Sagheer Abbas¹, Yousef Alhwaiti², Muhammad Saleem¹, Munir Ahmad¹, Muhammad Asif^1,*, Nouh Sabri Elmitwally^2,3

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 513-525, 2021, DOI:10.32604/iasc.2021.018770 - 11 August 2021

Abstract A Smart City understands the infrastructure, facilities, and schemes open to its citizens. According to the UN report, at the end of 2050, more than half of the rural population will be moved to urban areas. With such an increase, urban areas will face new health, education, Transport, and ecological issues. To overcome such kinds of issues, the world is moving towards smart cities. Cities cannot be smart without using Cloud computing platforms, the Internet of Things (IoT). The world has seen such incredible and brilliant ideas for rural areas and smart cities. While considering… More >

Nadia Tabassum¹, Tahir Alyas², Muhammad Hamid^3,*, Muhammad Saleem⁴, Saadia Malik⁵, Zain Ali², Umer Farooq²

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 175-186, 2021, DOI:10.32604/iasc.2021.018998 - 26 July 2021

Abstract Development in the field of opinion mining and sentiment analysis has been rapid and aims to explore views or texts on various social media sites through machine-learning techniques with the sentiment, subjectivity analysis and calculations of polarity. Sentiment analysis is a natural language processing strategy used to decide if the information is positive, negative, or neutral and it is frequently performed on literature information to help organizations screen brand, item sentiment in client input, and comprehend client needs. In this paper, two strategies for sentiment analysis is proposed for word embedding and a bag of… More >

Naeem Ali^1,*, Alia Ahmed¹, Leena Anum², Taher M. Ghazal^3,4, Sagheer Abbas⁵, Muhammad Adnan Khan^6,7, Haitham M. Alzoubi⁸, Munir Ahmad⁵

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 243-257, 2021, DOI:10.32604/iasc.2021.018983 - 26 July 2021

Abstract Information Collaboration of the supply chain is the domination and control of product flow information from the producer to the customer. The data information flow is correlated with demand fill-up, a role delivering service, and feedback. The collaboration of supply chain information is a complex contrivance that impeccably manages the efficiency flow and focuses on its vulnerable area. As there is always room for growth in the current century, major companies have shown a growing tendency to improve their supply chain’s productivity and sustainability to increase customer consumption in complying with environmental regulations. Therefore, in… More >

Naeem Ahmed Mahoto¹, Rabia Iftikhar¹, Asadullah Shaikh^2,*, Yousef Asiri², Abdullah Alghamdi², Khairan Rajab^2,3

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 147-159, 2021, DOI:10.32604/iasc.2021.018944 - 26 July 2021

Abstract The price of a product plays a vital role in its market share. Customers usually buy a product when it fits their needs and budget. Therefore, it is an essential area in the business to make decisions about prices for each product. The major portion of the business profit is directly connected with the percentage of the sale, which relies on certain factors of customers including customers’ behavior and market competitors. It has been observed in the past that machine learning algorithms have made the decision-making process more effective and profitable in businesses. The fusion… More >

Kathiravan Srinivasan¹, Lalit Garg^2,*, Bor-Yann Chen³, Abdulellah A. Alaboudi⁴, N. Z. Jhanjhi⁵, Chang-Tang Chang⁶, B. Prabadevi¹, N. Deepa¹

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 17-30, 2021, DOI:10.32604/iasc.2021.018380 - 26 July 2021

Abstract Expert Systems are interactive and reliable computer-based decision-making systems that use both facts and heuristics for solving complex decision-making problems. Generally, the cyclic voltammetry (CV) experiments are executed a random number of times (cycles) to get a stable production of power. However, presently there are not many algorithms or models for predicting the power generation stable criteria in microbial fuel cells. For stability analysis of Medicinal herbs’ CV profiles, an expert system driven by the augmented K-means clustering algorithm is proposed. Our approach requires a dataset that contains voltage-current relationships from CV experiments on the More >

Hao Wu^1,*, B. Nagaraj²

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 81-95, 2021, DOI:10.32604/iasc.2021.017654 - 26 July 2021

Abstract English teaching has always attracted much attention. However, the processes of its transmission and acquirement is often divided into two separate parts, which seriously hinders the effective implementation of its objectives. Teachers attach particular importance to the choice of the curriculum structure and teaching material. Students are busy comprehending the assignments their teachers deem important. Under such a scenario, the effective acquisition of knowledge and the development of sustainable comprehensive abilities are ignored. The random forest algorithm in machine learning applications could play important role improving on the current English teaching system. A random forest… More >

Adel Hamdan Mohammad^*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 65-80, 2021, DOI:10.32604/iasc.2021.016140 - 26 July 2021

Abstract Intrusion detection is an important topic that aims at protecting computer systems. Besides, feature selection is crucial for increasing the performance of intrusion detection. This paper employs a new hybrid feature selection model for intrusion detection. The implemented model uses Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms in a new manner. In addition, this study introduces two new models called (PSO-GWO-NB) and (PSO-GWO-ANN) for feature selection and intrusion detection. PSO and GWO show emergent results in feature selection for several purposes and applications. This paper uses PSO and GWO to select features… More >

Karpagam Sundararajan¹, Lalit Garg^2,*, Kathiravan Srinivasan^4,*, Ali Kashif Bashir³, Jayakumar Kaliappan⁴, Ganapathy Pattukandan Ganapathy⁵, Senthil Kumaran Selvaraj⁶, T. Meena⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 447-487, 2021, DOI:10.32604/cmes.2021.015528 - 22 July 2021

Abstract Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Its beginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughts in the last few decades. Predicting future droughts is vital for framing drought management plans to sustain natural resources. The data-driven modelling for forecasting the metrological time series prediction is becoming more powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques have demonstrated success in the drought prediction process and are becoming popular to More >