Mohammad Hamidi^1,*, Florentin Smarandache², Mohadeseh Taghinezhad¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1907-1923, 2024, DOI:10.32604/cmes.2023.030284

Abstract This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy (hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept. We have modeled the fuzzy superhypergraphs as complex superhypernetworks in order to make a relation between labeled objects in the form of details and generalities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzes them in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole to the whole group of objects at the same time.… More >

Salah-ud-din Khokhar^1,2,*, QinKe Peng¹, Muhammad Yasir Noor³

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2413-2427, 2023, DOI:10.32604/cmc.2023.036148

Abstract For fuzzy systems to be implemented effectively, the fuzzy membership function (MF) is essential. A fuzzy system (FS) that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output (SISO) FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s output. Utilizing a variety of non-linear techniques, a SISO FS is simulated. The results of FS experiments conducted in comparable conditions are then compared. The simulated results and the results of the experimental setup agree fairly well. The findings of the suggested model demonstrate that the relative… More >

W. J. Praiselin, J. Belwin Edward^*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1395-1415, 2023, DOI:10.32604/iasc.2023.028970

Abstract The contribution of Renewable Energy Resources (RER) in the process of power generation is significantly high in the recent days since it paves the way for overcoming the issues like serious energy crisis and natural contamination. This paper deals with the renewable energy based micro-grid as it is regarded as the apt solution for integrating the RER with the electrical frameworks. As the fixed droop coefficients in conventional droop control approaches have caused various limitations like low power-sharing and sudden drops of grid voltage in the Direct Current (DC) side, the Harmonized Membership Fuzzy Logic (MFL) droop control is employed… More >

Alamelu Manghai T Marimuthu¹, Jegadeeshwaran Rakkiyannan^2,*, Lakshmipathi Jakkamputi¹, Sugumaran Vaithiyanathan¹, Sakthivel Gnanasekaran²

Structural Durability & Health Monitoring, Vol.16, No.4, pp. 383-396, 2022, DOI:10.32604/sdhm.2022.011396

Abstract The requirement of fault diagnosis in the field of automobiles is growing higher day by day. The reliability of human resources for the fault diagnosis is uncertain. Brakes are one of the major critical components in automobiles that require closer and active observation. This research work demonstrates a fault diagnosis technique for monitoring the hydraulic brake system using vibration analysis. Vibration signals of a rotating element contain dynamic information about its health condition. Hence, the vibration signals were used for the brake fault diagnosis study. The study was carried out on a brake fault diagnosis experimental setup. The vibration signals… More >

Monika Khandelwal¹, Ranjeet Kumar Rout¹, Saiyed Umer², Kshira Sagar Sahoo³, NZ Jhanjhi^4,*, Mohammad Shorfuzzaman⁵, Mehedi Masud⁵

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3587-3598, 2023, DOI:10.32604/iasc.2023.029785

Abstract Classification of the patterns is a crucial structure of research and applications. Using fuzzy set theory, classifying the patterns has become of great interest because of its ability to understand the parameters. One of the problems observed in the fuzzification of an unknown pattern is that importance is given only to the known patterns but not to their features. In contrast, features of the patterns play an essential role when their respective patterns overlap. In this paper, an optimal fuzzy nearest neighbor model has been introduced in which a fuzzification process has been carried out for the unknown pattern using… More >

Ashit Kumar Dutta^1,*, Yasser Albagory², Farhan M. Obesat³, Anas Waleed Abulfaraj⁴

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1659-1674, 2022, DOI:10.32604/iasc.2022.026263

Abstract Energy is considered a valuable source in wireless sensor networks (WSN) for effectively improving the survivability of the network. The non-uniform dispersion of load in the network causes unbalanced energy dissipation which can result in network interruption. The route selection process can be considered as an optimization problem and is solved by utilize of artificial intelligence (AI) techniques. This study introduces an energy efficient chaotic krill herd algorithm with adaptive neuro fuzzy inference system based routing (EECKHA-ANFIS) protocol for WSN. The goal of the EECKHA-ANFIS method is for deriving a better set of routes to destination in such a way… More >

Muhammad Hamza Azam¹, Mohd Hilmi Hasan^1,*, Azlinda A Malik², Saima Hassan³, Said Jadid Abdulkadir¹

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1799-1815, 2022, DOI:10.32604/cmc.2022.028292

Abstract Electricity price forecasting is a subset of energy and power forecasting that focuses on projecting commercial electricity market present and future prices. Electricity price forecasting have been a critical input to energy corporations’ strategic decision-making systems over the last 15 years. Many strategies have been utilized for price forecasting in the past, however Artificial Intelligence Techniques (Fuzzy Logic and ANN) have proven to be more efficient than traditional techniques (Regression and Time Series). Fuzzy logic is an approach that uses membership functions (MF) and fuzzy inference model to forecast future electricity prices. Fuzzy c-means (FCM) is one of the popular… More >

E. Kavitha^1,*, R. Tamilarasan², Arunadevi Baladhandapani³, M. K. Jayanthi Kannan⁴

Computer Systems Science and Engineering, Vol.43, No.3, pp. 871-886, 2022, DOI:10.32604/csse.2022.021215

Abstract Gene expression data represents a condition matrix where each row represents the gene and the column shows the condition. Micro array used to detect gene expression in lab for thousands of gene at a time. Genes encode proteins which in turn will dictate the cell function. The production of messenger RNA along with processing the same are the two main stages involved in the process of gene expression. The biological networks complexity added with the volume of data containing imprecision and outliers increases the challenges in dealing with them. Clustering methods are hence essential to identify the patterns present in… More >

Jumana Alsubhi¹, Abdulrahman Gharawi¹, Mohammad Alahmadi^2,*

Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 193-200, 2021, DOI:10.32604/jihpp.2021.027871

Abstract Nowadays, machine learning (ML) algorithms cannot succeed without the availability of an enormous amount of training data. The data could contain sensitive information, which needs to be protected. Membership inference attacks attempt to find out whether a target data point is used to train a certain ML model, which results in security and privacy implications. The leakage of membership information can vary from one machine-learning algorithm to another. In this paper, we conduct an empirical study to explore the performance of membership inference attacks against three different machine learning algorithms, namely, K-nearest neighbors, random forest, support vector machine, and logistic… More >

Nguyen A. Tuan¹, D. Akila², Souvik Pal³, Bikramjit Sarkar⁴, Thien Khai Tran¹, G. Mothilal Nehru², Dac-Nhuong Le^5,6,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1357-1372, 2022, DOI:10.32604/cmc.2022.024096

Abstract This article presents a new scheme for dynamic data optimization in IoT (Internet of Things)-assisted sensor networks. The various components of IoT assisted cloud platform are discussed. In addition, a new architecture for IoT assisted sensor networks is presented. Further, a model for data optimization in IoT assisted sensor networks is proposed. A novel Membership inducing Dynamic Data Optimization Membership inducing Dynamic Data Optimization (MIDDO) algorithm for IoT assisted sensor network is proposed in this research. The proposed algorithm considers every node data and utilized membership function for the optimized data allocation. The proposed framework is compared with two stage… More >