Chandraumakantham Om Kumar^1,*, Sudhakaran Gajendran², Suguna Marappan¹, Mohammed Zakariah³, Abdulaziz S. Almazyad⁴

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 471-501, 2024, DOI:10.32604/cmc.2024.054966 - 15 October 2024

Abstract The security of the wireless sensor network-Internet of Things (WSN-IoT) network is more challenging due to its randomness and self-organized nature. Intrusion detection is one of the key methodologies utilized to ensure the security of the network. Conventional intrusion detection mechanisms have issues such as higher misclassification rates, increased model complexity, insignificant feature extraction, increased training time, increased run time complexity, computation overhead, failure to identify new attacks, increased energy consumption, and a variety of other factors that limit the performance of the intrusion system model. In this research a security framework for WSN-IoT, through… More >

Jiqiang Chen, Ranran Han, Dongqing Zhang, Litao Ma^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5067-5082, 2024, DOI:10.32604/cmc.2024.051494 - 20 June 2024

Abstract Imbalanced datasets are common in practical applications, and oversampling methods using fuzzy rules have been shown to enhance the classification performance of imbalanced data by taking into account the relationship between data attributes. However, the creation of fuzzy rules typically depends on expert knowledge, which may not fully leverage the label information in training data and may be subjective. To address this issue, a novel fuzzy rule oversampling approach is developed based on the learning vector quantization (LVQ) algorithm. In this method, the label information of the training data is utilized to determine the antecedent… More >

A. Manju¹, A. Revathi², M. Arivukarasi¹, S. Hariharan³, V. Umarani⁴, Shih-Yu Chen^5,*, Jin Wang⁶

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 905-920, 2023, DOI:10.32604/iasc.2023.038444 - 29 April 2023

Abstract With the proliferation of the internet, big data continues to grow exponentially, and video has become the largest source. Video big data introduces many technological challenges, including compression, storage, transmission, analysis, and recognition. The increase in the number of multimedia resources has brought an urgent need to develop intelligent methods to organize and process them. The integration between Semantic link Networks and multimedia resources provides a new prospect for organizing them with their semantics. The tags and surrounding texts of multimedia resources are used to measure their semantic association. Two evaluation methods including clustering and… More >

Ahmed Abdu Alattab^1,*, Mohammed Eid Ibrahim¹, Reyazur Rashid Irshad¹, Anwar Ali Yahya², Amin A. Al-Awady³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2397-2413, 2023, DOI:10.32604/cmc.2023.030924 - 31 October 2022

Abstract This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed More >

Wenjia Xiang¹, Xiaoyu Li^1,*, Zirui He¹, Chenjing Su¹, Wangchi Cheng², Chao Lu³, Shan Yang⁴

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3627-3639, 2023, DOI:10.32604/iasc.2023.030904 - 17 August 2022

Abstract Estimating the intention of space objects plays an important role in aircraft design, aviation safety, military and other fields, and is an important reference basis for air situation analysis and command decision-making. This paper studies an intention estimation method based on fuzzy theory, combining probability to calculate the intention between two objects. This method takes a space object as the origin of coordinates, observes the target’s distance, speed, relative heading angle, altitude difference, steering trend and etc., then introduces the specific calculation methods of these parameters. Through calculation, values are input into the fuzzy inference More >

Praveen Talari^1,*, A. Suresh², M. G. Kavitha³

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1053-1067, 2023, DOI:10.32604/iasc.2023.027024 - 06 June 2022

Abstract As per World Health Organization report which was released in the year of 2019, Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world. Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it. Among the diabetics, it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.… More >

T. Mithila^1,*, R. Arunprakash², A. Ramachandran³

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1165-1179, 2022, DOI:10.32604/csse.2022.023308 - 08 February 2022

Abstract In today’s real world, an important research part in image processing is scene text detection and recognition. Scene text can be in different languages, fonts, sizes, colours, orientations and structures. Moreover, the aspect ratios and layouts of a scene text may differ significantly. All these variations appear assignificant challenges for the detection and recognition algorithms that are considered for the text in natural scenes. In this paper, a new intelligent text detection and recognition method for detectingthe text from natural scenes and forrecognizing the text by applying the newly proposed Conditional Random Field-based fuzzy rules… More >

Sunil Kr. Jha¹, Zulfiqar Ahmad²

CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.4, pp. 443-459, 2017, DOI:10.3970/cmes.2017.113.443

Abstract Microbial population and enzyme activities are the significant indicators of soil strength. Soil microbial dynamics characterize microbial population and enzyme activities. The present study explores the development of efficient predictive modeling systems for the estimation of specific soil microbial dynamics, like rock phosphate solubilization, bacterial population, and ACC-deaminase activity. More specifically, optimized subtractive clustering (SC) and Wang and Mendel's (WM) fuzzy inference systems (FIS) have been implemented with the objective to achieve the best estimation accuracy of microbial dynamics. Experimental measurements were performed using controlled pot experiment using minimal salt media with rock phosphate as More >