Journal of Intelligent & Fuzzy Systems - Volume 36, issue 3

Authors: Zhang, Qinghua | Liu, Kaixuan | Feng, Lin

Article Type: Research Article

Abstract: Rough set theory proposed by professor Pawlak in 1982 is an important tool to solve uncertain problems. In order to make rough sets deal with uncertain problems better, by considering the stringent notions of mathematical equality and inclusion, the definitions of rough equality and rough inclusion were introduced by Pawlak. But the researches of rough equality and rough inclusion are on a certain granularity space. In this paper, some change rules will be given with respect to the relations of rough equality and rough inclusion between two uncertain target sets in multi-granulation spaces, and the similarity degree between two roughly …equal sets is proposed to describe the similarity of two uncertain sets in multi-granulation spaces. In order to describe two uncertain sets which are rough equality by an approximation set at the same time, the definitions of optimistic λ -approximation set and pessimistic λ -approximation set will be defined from the points of optimism and pessimism, and some properties of them are discussed in detail. Show more

Keywords: Rough set, rough equality, rough inclusion, similarity, multi-granulation spaces, approximation set

DOI: 10.3233/JIFS-181221

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2793-2806, 2019

Authors: Khorrami, Niyaz | Shamloo, Ali Salimi | Parsa Moghaddam, Behrouz

Article Type: Research Article

Abstract: In this paper, Nystrom method was used to solve the Fredholm integral equations of the second kind under interval data. The interval analysis is first presented along with integral equations of the second kind and then Nystrom method is used to find solution of integral equations in the intervals instead of nodes. Also the existence of solution and error analysis is presented. Numerical examples show that the method is efficient and demonstrate a good accuracy.

Keywords: intervals, Interval computations, Fredholm integral equation of the second kind, Nystrom method under interval data.

DOI: 10.3233/JIFS-181206

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2807-2816, 2019

Authors: Al-Mejibli, Intisar | Ismail, Sura F.

Article Type: Research Article

Abstract: The issues of security and privacy in multimedia data have become of most extreme significance particularly in the applications associated to medical and military sectors. In this paper, an innovative encryption algorithm for real time videos is proposed. The proposed algorithm consists of two phases in both sender and receiver sides. In these two phases, the tasks of compression/encryption and decompression /decryption are performed at sender and receiver sides respectively. The proposal uses H.261 codec in compression/decompression processes and chaotic logistic map system in encryption/decryption processes for private – key generation. The suggested algorithm takes the features of H.261 codec …into consideration to achieve high security with less processing time by encrypt the produced intra frame (I frame) and leaving inter-frame (P-frame) without any changing. Proposed algorithm has innovated new strategy in selecting bytes for encryption by encrypt half of bytes in each I-frame or all of them. Most common statistical tests were performed on the obtained results from applying the proposed algorithm and the results were promising in terms of security level and required time for performing two states. Show more

Keywords: Chaotic logistic map, decryption, encryption, H.261, real-time video

DOI: 10.3233/JIFS-171966

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2817-2827, 2019

Authors: Ashraf, Shahzaib | Abdullah, Saleem | Mahmood, Tahir | Ghani, Fazal | Mahmood, Tariq

Article Type: Research Article

Abstract: The key objective of the present proposed work in this paper is introduced a new version of picture fuzzy set so called spherical fuzzy sets (SFS). spherical fuzzy set is a new extension of picture fuzzy sets and Pythagorean fuzzy sets. In spherical fuzzy sets, membership degrees are gratifying the condition 0 ⩽ P 2 (x ) + I 2 (x ) + N 2 (x ) ⩽1 instead of 0 ⩽ P (x ) + I (x ) + N (x ) ⩽1 as is in picture fuzzy sets. In this paper, we …investigate the basic operations of spherical fuzzy sets and discuss some related results. We extend operational laws to aggregation operators and introduce weighted averaging and weighted geometric aggregation operators based on spherical fuzzy number’s. Further a multi attribute decision making method is developed and these aggregation operators are utilized. Finally, we constructed a numerical approach for implementation of proposed technique. Show more

Keywords: Spherical fuzzy sets, aggregation operators, multi-attribute decision making problem

DOI: 10.3233/JIFS-172009

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2829-2844, 2019

Authors: Khodsuz, Masume | Seyyedbarzegar, Seyyedmeysam

Article Type: Research Article

Abstract: Surge arresters are essential equipment for power system protection against transient overvoltages. Therefore, their operating condition and fault diagnosis are very important. Leakage current analysis is a conventional method of surge arrester condition monitoring. In this paper, the impacts of disruptive factors on harmonic components of surge arrester current have been evaluated experimentally. Experimental tests have been done on different surge arresters to investigate disruptive factors effects on surge arresters leakage current. To show the ability of introduced indicators, obtained dataset was applied to fuzzy network for recognition task and classification. In order to increase the accuracy of proposed system, …the optimum vector of radius has been found using the optimization algorithm. Bees algorithm, genetic algorithm, imperialist competitive algorithm and particle swarm optimization have been applied to evolve adaptive network based fuzzy inference system. Also the performance of adaptive network based fuzzy inference system has been compared with other classifiers to investigate the capability of the proposed classifier. Results show that the success rates of Bees-ANFIS is higher than the performance of other systems. Show more

Keywords: Surge arrester, harmonics analysis, leakage current, adaptive network based fuzzy inference system, bees algorithm

DOI: 10.3233/JIFS-172040

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2845-2855, 2019

Authors: Javidsharifi, Mahshid | Niknam, Taher | Aghaei, Jamshid | Mokryani, Geev | Papadopoulos, Panagiotis

Article Type: Research Article

Abstract: Investigation of the environmental/economic optimal operation management of a microgrid (MG) as a case study for applying a novel modified multi-objective grey wolf optimizer (MMOGWO) algorithm is presented in this paper. MGs can be considered as a fundamental solution in order for distributed generators’ (DGs) management in future smart grids. In the multi-objective problems, since the objective functions are conflict, the best compromised solution should be extracted through an efficient approach. Accordingly, a proper method is applied for exploring the best compromised solution. Additionally, a novel distance-based method is proposed to control the size of the repository within an aimed …limit which leads to a fast and precise convergence along with a well-distributed Pareto optimal front. The proposed method is implemented in a typical grid-connected MG with non-dispatchable units including renewable energy sources (RESs), along with a hybrid power source (micro-turbine, fuel-cell and battery) as dispatchable units, to accumulate excess energy or to equalize power mismatch, by optimal scheduling of DGs and the power exchange between the utility grid and storage system. The efficiency of the suggested algorithm in satisfying the load and optimizing the objective functions is validated through comparison with different methods, including PSO and the original GWO. Show more

Keywords: Multi objective optimal operation management, pareto optimal solution, modified grey wolf optimizer, micro-grid, renewable energy sources

DOI: 10.3233/JIFS-171688

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2857-2870, 2019

Authors: Tran, Tien Anh

Article Type: Research Article

Abstract: Navigable environment can impact on the energy efficiency of ships. The reasonable operation with ships can be achieved the purpose of energy saving and emission reduction under different navigation environment. In this paper, a bulk carrier is chosen as the research object. According to experimental data, the fuel consumption level is analyzed in different wave height, wind speed and ship operation mode by using the fuzzy clustering method. The data analysis will show that in different navigation environments, the reasonable operation of ships can significantly improve the ship energy efficiency.

Keywords: Bulk carriers, energy efficiency of ships, fuzzy clustering method, navigation environment, fuel consumption of engine

DOI: 10.3233/JIFS-171698

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2871-2884, 2019

Authors: Liang, Chengyu | Li, Fanghui

Article Type: Research Article

Abstract: In this paper, S 0 , S 1 and S 2 separation axioms are introduced in M -fuzzifying convex spaces. Each M -fuzzifying convex space can be regarded to be S 0 , S 1 and S 2 separated to some degree. Some properties of them are investigated. The relations among them are discussed.

Keywords: M-fuzzifying convex spaces, S0 , S1 , S2

DOI: 10.3233/JIFS-171361

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2885-2893, 2019

Authors: Hsu, Ming-Fu

Article Type: Research Article

Abstract: Due to the radical changes in the global economy and internationalization of markets around the world, local corporates are encountering much more severe challenges and uncertainties than ever before. Hence, how to reliably and effectively evaluate whether corporates will exhibit substantial troubles/difficulties in the near future turns out to be an attractive investigative issue. This study introduces a fusion mechanism that gives decision makers a comprehensive description on a corporate’s operation status so as to prevent a biased judgment from occurring. The introduced mechanism consists of three main procedures: (1) Performance rank determination through the integration of balanced scorecards (BSC) …and two-level DEA with a weighting adjusted strategy; (2) Forecasting model construction by combining core vector machine (CVM) with the support vectors (SV)-based online learning strategy; and (3) Knowledge extraction by a rule-based algorithm. The experimental results show that the introduced fusion mechanism (i.e., TDMCR) reduces unnecessary information, gives a more overarching description, satisfactorily predicts a corporate’s operation status, and provides intuitive decision logics for market participators to adjust their investment portfolios for maximizing their profit margins under an anticipated risk level. Examined by real cases, the introduced fusion mechanism is a promising alternative for corporate operating performance forecasting. Show more

Keywords: Risk management, multiple-attribute decision making, forecasting, management decision

DOI: 10.3233/JIFS-171366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2895-2905, 2019

Authors: Kadri, Muhammad Bilal

Article Type: Research Article

Abstract: Two-stage model free fuzzy adaptive control (MFFAC) has been proposed which rejects the multiplicative input disturbance while also reducing the unnecessary control activity arising due to the sensor noise. Noisy sensor measurements of the input disturbance severely degrades the control performance and might destabilize the control loop. In this work, a novel approach has been proposed which initially develops a model of the multiplicative input disturbance whereas in the second stage the measurement uncertainty is modeled. The uncertainty is ultimately represented as the fuzziness of the control signal. Adaptive conditional defuzzification is employed which utilizes the fuzziness resulting in reduced …control activity. The proposed control scheme has shown good control performance in cases where the plant dynamics varies and the sensor noise in the control loop cannot be simply rejected by low pass filtering. Simulation and experimental results adequately validate the effectiveness of the proposed approach. Show more

Keywords: Model free neuro-fuzzy controller, noise multiplicative disturbance rejection, adaptive conditional defuzzification

DOI: 10.3233/JIFS-171548

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2907-2922, 2019