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 >

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 >

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 >

Shruti Jain¹, Cherry Bhargava², Vijayakumar Varadarajan³, Ketan Kotecha^4,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1815-1829, 2022, DOI:10.32604/cmc.2022.024004

Abstract In the recent decade, different researchers have performed hardware implementation for different applications covering various areas of experts. In this research paper, a novel analog design and implementation of different steps of fuzzy systems with current differencing buffered amplifier (CDBA) are proposed with a compact structure that can be used in many signal processing applications. The proposed circuits are capable of wide input current range, simple structure, and are highly linear. Different electrical parameters were compared for the proposed fuzzy system when using different membership functions. The novelty of this paper lies in the electronic implementation of different steps for… More >

Xiaolan Guo¹, Chenyan Liu¹, Muhammad Shakeel², Delu Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.91, No.6, pp. 1289-1302, 2022, DOI:10.32604/phyton.2022.019774

Abstract The root system plays an important role in the growth and development of blueberry. The aim of this study was to assess the impacts of different fertilizers on the root growth and root–yield relationship of blueberry to provide insight into the regulation of root growth and fruit yield by fertilizing from the perspective of the root system. Rabbiteye blueberry variety ‘Britewell’ as the test material, and six fertilizers, including BF, OR, CF, SF, HF, and RT were used in single-factor fertilization experiments to analyze the effects of different fertilizer treatments on the root morphology, root distribution, and fruit yield of… More >

Siti Hajar Khairuddin, Mohd Hilmi Hasan^*, Emilia Akashah P. Akhir, Manzoor Ahmed Hashmani

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 717-734, 2022, DOI:10.32604/cmc.2022.020666

Abstract Fuzzy inference system (FIS) is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs. The system starts with identifying input from data, applying the fuzziness to input using membership functions (MF), generating fuzzy rules for the fuzzy sets and obtaining the output. There are several types of input MFs which can be introduced in FIS, commonly chosen based on the type of real data, sensitivity of certain rule implied and computational limits. This paper focuses on the construction of interval type 2 (IT2) trapezoidal shape MF from fuzzy C Means (FCM) that is used for… More >

Yilin Bi¹, Yuxin Ouyang¹, Guang Sun¹, Peng Guo^{1, 2}, Jianjun Zhang³, Yijun Ai^{1, *}

Journal on Big Data, Vol.2, No.1, pp. 9-18, 2020, DOI:10.32604/jbd.2020.01002

Abstract The arrival of big data era has brought new opportunities and challenges to the development of various industries in China. The explosive growth of commercial bank data has brought great pressure on internal audit. The key audit of key products limited to key business areas can no longer meet the needs. It is difficult to find abnormal and exceptional risks only by sampling analysis and static analysis. Exploring the organic integration and business processing methods between big data and bank internal audit, Internal audit work can protect the stable and sustainable development of banks under the new situation. Therefore, based… More >

Zichun Yang^1,2,3, Kunfeng Li^1,4, Qi Cai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.95, No.2, pp. 143-171, 2013, DOI:10.3970/cmes.2013.095.143

Abstract The conventional probabilistic reliability model for structures is based on the “probability assumption” and “binary-state assumption”. These assumptions are often offset the reality of practical engineering and lead to a wrong conclusion. In fact, besides randomness, fuzziness which is different from randomness in nature is also a prevalent uncertainty factor and plays an important role in structural reliability assessment. In this paper, a novel structural reliability model with random variables and fuzzy variables is established by using the fuzzy set theory, possibility theory and probability measure for fuzzy events, based on the “mixed probability and possibility assumption” and “fuzzy state… More >

Şahin Emrah Amrahov¹, Iman N.Askerzade¹

CMES-Computer Modeling in Engineering & Sciences, Vol.70, No.1, pp. 1-10, 2010, DOI:10.3970/cmes.2010.070.001

Abstract In this paper we define multivariable fuzzy functions (MFF) and corresponding multivariable crisp functions (MCF). Then we give a definition for the maximum value of MFF, which in some cases coincides with the maximum value in Pareto sense. We introduce generalized maximizing and minimizing sets in order to determine the maximum values of MFF. By equating membership functions of a given fuzzy domain set and the corresponding maximizing set, we obtain a curve of equal possibilities. Then we use the method of Lagrange multipliers to solve the resulting nonlinear optimization problem when the membership functions are differentiable. We finally present… More >