Journal of Intelligent & Fuzzy Systems - Volume Preprint, issue Preprint

Authors: Jiang, Ping | Dou, Quansheng | Hu, Xiaoying

Article Type: Research Article

Abstract: This paper presents a supervised method for blood vessel segmentation in digital retinal images by a combination of learning and classification. For an image, the method defines and computes pixel strength as primary features for conservatively computing vessel and background pixels as preliminary segmentation, from which the main segmentation selects training data to learn a neutral network (NN) classifier on the fly. Each pixel in the training data set is represented by an 8-D vector composed of intensity descriptor and pixel strength features, and the learned classifier for the image is next applied to classify the undetermined pixels. The segmentation …results are further refined by filtering out the outliers. The method was evaluated on the publicly available DRIVE database, and the results showed better or comparable performance when comparing with other existing solutions in literature. The much better sensitivity and robustness of our approach with different image conditions make it potentially suitable for clinical applications such as automated screening for early diabetic retinopathy detection, and auto- and semi-automatic grading of diabetic retinopathy. Show more

Keywords: Vessel segmentation, learning and classification, pixel strength, neural network

DOI: 10.3233/IFS-151812

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-11, 2015

Authors: Feng, Yanpeng | Wu, Bo

Article Type: Research Article

Abstract: To address the problem that reactive navigation is prone to local optimality under uncertain and complex environments, a POMDP-based global path planning algorithm is proposed for mobile robots. A 6-tuple model is constructed for path planning under complex dynamic environments, and the global optimality is realizes by maximizing the accumulative reward function. State transition function and observation function are used to handle unknown obstacles and noisy perception by modeling the error probability. Belief state space is introduced, and a value iteration algorithm using point-based policy tree pruning is developed to solve for real time planning policy, which effectively reduces the …computational complexity. Simulation results show that using this algorithm the robot can automatically adapt to different probing granularities, avoid obstacles under complex uncertain environments, and achieve the optimal paths. Show more

Keywords: Mobile robot, path planning, grid method, POMDP, belief state, policy

DOI: 10.3233/JIFS-169337

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-6, 2017

Authors: Karaşan, Ali | Kahraman, Cengiz

Article Type: Research Article

Abstract: Location selection for a freight village is extremely important since it has strong impacts on quality of life such as reduction of traffic congestion, reduction of carbon emission, and effective use of lands. The inclusion of such criteria in a location selection requires the fuzzy sets to be used in the decision making methodology. In this paper, we propose a novel integrated fuzzy decision model for the location selection of freight villages. In this integrated methodology, we use DEMATEL for determining the most effective criteria and their inner and outer dependencies; ANP for weighting the determined criteria; and TOPSIS for …finding the best location alternative. The proposed model is applied to a case study for the city of Istanbul in Turkey. Show more

Keywords: Intuitionistic fuzzy sets, DEMATEL, ANP, TOPSIS, freight village

DOI: 10.3233/JIFS-17169

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-18, 2017

Authors: Solovyev, Valery | Ivanov, Vladimir | Solnyshkina, Marina

Article Type: Research Article

Abstract: In this paper we explore to what extent text parameters, such as average number of words per sentence, syllables per word, nouns per sentence, frequency of content words, etc. can successfully rank Russian academic texts for different age and grade levels. We provide a brief overview of previous research on readability of Russian texts and describe the corpus of school textbooks on Social Studies (from 5-th to 11-th grade) compiled by the authors. We share our experience of using a variety of quantitative text complexity metrics and evaluate the measures of existing Russian text complexity formulas. Based on the tests …of a set of extended text features, we propose one innovative metric for better prediction of Russian text complexity, i.e. the number of adjectives. As the results obtained compare favorably with the previously published results on the established complexity metrics for Russian texts, the study encourages the development of valid, reliable and transparent complexity tools for Russian texts. Show more

Keywords: Text complexity, readability of academic text, Russian language, readability formulas

DOI: 10.3233/JIFS-169489

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-10, 2018

Authors: Hemanth, D. Jude | Anitha, J. | Popescu, Daniela Elena | Son, Le Hoang

Article Type: Research Article

Abstract: Image steganography plays a vital role in hiding significant secret information within any input image. Numerous steganography techniques have been carried out to hide the secret information in images. In the current scenario, frequency domain techniques are widely preferred which are mostly transform based approaches. Conventionally, the secret data is hidden randomly in the coefficients of the transformed image. However, such random data hiding techniques lead to inferior performance of the overall system. Thus, using an optimization algorithm is obligatory to find out the optimal coefficients. Genetic Algorithm (GA) is normally used for selecting the optimal transform coefficients to enhance …the system performance. However, conventional GA based approaches are highly random in nature which again leads to inaccurate results. In this work, a modified GA approach was proposed to determine the optimal coefficients in order to improve the embedding capacity and stego image quality. The achieved average peak signal to noise ratio (PSNR) was 50.29 dB with embedding capacity of 139361 bits. These experimental results validate the practical feasibility of the proposed methodology for image steganography. Show more

Keywords: Fresnelet transform, frequency domain steganography, genetic algorithm, modified genetic algorithm, embedding capacity and peak signal to noise ratio

DOI: 10.3233/JIFS-169580

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-13, 2018

Authors: Saravanan, M. | Sujatha, R. | Sundareswaran, R. | Sahoo, Sankar | Pal, Madhumangal

Article Type: Research Article

Abstract: The stability of a network is measured by vulnerability parameters. Integrity is one the most important vulnerability parameter in the field of graph network. An uncertain network can be modeled as a fuzzy graph. In this paper, vertex integrity of fuzzy graph is introduced and illustrated with example. Also, we introduced the vertex integrity of the union, join and Cartesian product of two fuzzy graphs and established many interesting results on them. Finally, we discussed edge integrity of fuzzy graph with suitable illustration and investigated many results on edge integrity of fuzzy graph.

Keywords: Vertex integrity, edge integrity, join of fuzzy graph, cartesian product of fuzzy graph, union of fuzzy graph

DOI: 10.3233/JIFS-171685

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-11, 2018

Authors: Tang, Gang | Zhang, Yao | Wang, Huaqing

Article Type: Research Article

Abstract: The prediction of performance degradation is significant for the health monitoring of rolling bearing, which helps to greatly reduce the loss caused by potential faults in the entire life cycle of rotating machinery. As a new method of machine learning based on statistical learning theory, a so-called multivariable least square support vector machines (LS-SVM) was developed. However, it is unsatisfactory for the prediction of performance degradation without adequate consideration of time variation and data volatility, which are notable features of the obtained time series signal from bearings. To overcome these problems, a new multivariable LS-SVM with a moving window over …time slices is proposed. In this model, different features over time slices are extracted through a moving window to construct new sample pairs according to the embedding theory. The model adaptability is also improved through an iterative updating strategy. Furthermore, the algorithm parameters are optimized using coupled simulated annealing to improve the prediction accuracy. Bearing fault experiments show that the proposed model outperforms the general multivariable LS-SVM. Show more

Keywords: Multivariable least square support vector machines, performance degradation prediction, time slices, moving window

DOI: 10.3233/JIFS-169548

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-11, 2018

Authors: Avilés-Ochoa, Ezequiel | León-Castro, Ernesto | Alessandri Perez-Arellano, Luis | Merigó, José M.

Article Type: Research Article

Abstract: The prioritized induced probabilistic ordered weighted average distance (PIPOWAD) has been developed. This new operator is an extension of the ordered weighted average (OWA) operator that can be used in cases where we have two sets of data that want to be compared. Some of the main characteristics of this new operator are: 1) Not all the decision makers are equally important, so the information needs to be prioritized, 2) The information has a probability to occur and 3) The decision makers can change the importance of the information based in an induced variable. Additionally, characteristics and families of the …PIPOWAD operator are presented. Finally, an application of the PIPOWAD operator in order to measure government transparency in Mexico is presented. Show more

Keywords: OWA operator, prioritized aggregation operators, induced aggregation operators, probabilistic aggregation operators, transparency and access to information

DOI: 10.3233/JIFS-17935

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-12, 2018

Authors: Fahmi, A. | Abdullah, S. | Amin, F. | Ahmed, R. | Ali, A.

Article Type: Research Article

Abstract: In this paper, we define aggregation operators for triangular cubic linguistic hesitant fuzzy sets which includes generalized triangular cubic linguistic hesitant fuzzy weighted averaging (GTCLHFWA) operator, generalized triangular cubic linguistic hesitant fuzzy weighted geometric (GTCHFWG) operator, generalized triangular cubic linguistic hesitant fuzzy ordered weighted average (GTCLHFOWA) operator, generalized triangular cubic linguistic hesitant fuzzy ordered weighted geometric (GTCLHFOWG) operator, generalized triangular cubic linguistic hesitant fuzzy hybrid averaging (GTCLHFHA) operator and generalized triangular cubic linguistic hesitant fuzzy hybrid geometric (GTCLHFHG) operator. Furthermore, we relate these aggregation operators to develop an approach to multiple attribute group decision-making with triangular cubic linguistic hesitant fuzzy …information. Finally, a numerical example is providing to demonstrate the submission of the established approach. Show more

Keywords: Triangular cubic linguistic fuzzy sets and triangular cubic linguistic fuzzy numbers, aggregation triangular cubic linguistic hesitant fuzzy information, an approach to multiple attribute group decision-making with triangular cubic linguistic hesitant fuzzy information, the application of the developed approach in group decision-making problems

DOI: 10.3233/JIFS-171567

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-15, 2018

Authors: Qu, Guohua | Wang, Yunhuan | Qu, Weihua | Li, Chunhua | Zhou, Haisheng

Article Type: Research Article

Abstract: (DHFNs) are very suitable to be used for depicting membership function and non-membership function in uncertain event. Motivated by the idea of Shapley-Choquet integral [Meng et al. Generalized hesitant fuzzy generalized Shapley-Choquet integral operators and their application in decision making, International Journal of Fuzzy Systems 16 (3) (2014), 400–410], in this paper we develop two Shapley generalized dual hesitant fuzzy generalized Choquet integral operators which globally consider the importance of elements in a set, and the correlations among them. Some important properties of the two operators are examined and apply them to develop an approach to dual hesitant fuzzy …multi-attribute decision making with incomplete weight information. Moreover, A new distance measure of DHFSs is defined. If the information about the weights of attributes is incompletely known, the model for the optimal fuzzy measure on attribute set is established Finally, two numerical examples are given in solving decision making problems and the results demonstrate the feasibility and effectiveness of using the two Shapley generalized dual hesitant fuzzy generalized Choquet integral operators. Show more

Keywords: Multi-attribute decision making, dual hesitant fuzzy element, fuzzy measure, Choquet integral, generalized Shapley function

DOI: 10.3233/JIFS-171837

Citation: Journal of Intelligent & Fuzzy Systems, vol. Preprint, no. Preprint, pp. 1-17, 2018