Journal of Intelligent & Fuzzy Systems - Volume 41, issue 1

Authors: Yue, Xiaofeng | Ma, Guoyuan | Liu, Fuqiuxuan | Gao, Xueliang

Article Type: Research Article

Abstract: Due to the complexity and variety of textures on Strip steel, it is very difficult to detect defects on rigid surfaces. This paper proposes a metal surface defect classification method based on an improved bat algorithm to optimize BP neural network. First, this paper uses the Local Binary Pattern(LBP) algorithm to extract features from six types of defect images including inclusion, patches, crazing, pitted, rolled-in, and scratches, and build a feature sample library with the extracted feature values. Then, the WG-BA-BP network is used to classify the defect images with different characteristics. The weighted experience factor added by the network …can control the flight speed of the bat according to the number of iterations and the change of the fitness function. And the gamma distribution is added in the process of calculating loudness, which enhances the local searchability. The BP network optimized by this method has higher accuracy. Finally, to verify the effectiveness of the method, this article introduces the five evaluation indicators of accuracy, precision, sensitivity, specificity, and F1 value under the multi-class model. To prove that this algorithm is more feasible and effective compared with other swarm intelligence algorithms. The best prediction performance of WG-BA-BP is 0.010905, and the accuracy rate can reach 0.9737. Show more

Keywords: Image classification, BP neural network, Bat Algorithm, weighted experience factor, Gamma distribution

DOI: 10.3233/JIFS-210374

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1509-1521, 2021

Authors: Aslam, Muhammad | Albassam, Mohammed

Article Type: Research Article

Abstract: In this paper, tests of skewness and kurtosis are introduced under neutrosophic statistics. The necessary measures and neutrosophic forms of these estimators are introduced. The application of the proposed tests is given using the data associated with heart diseases. From the real example analysis, the proposed tests are quite flexible and informative than the existing tests under classical statistics. In addition, it is concluded from the analysis that the proposed tests give information about the measure of indeterminacy in the presence of uncertainty.

Keywords: Skewness, kurtosis, normality, Neutrosophy, heart disease

DOI: 10.3233/JIFS-210375

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1523-1529, 2021

Authors: Li, Baolin | Yang, Lihua

Article Type: Research Article

Abstract: Picture fuzzy set (PFS) and linguistic term set (LTS) are two significant notions in multi-criteria decision-making (MCDM). In practice, decision-makers sometimes need utilize the multiple probable membership degrees for an uncertain linguistic term to express evaluation information. Motivated by these, to better convey the vagueness and uncertainty of cognitive information, multi-valued picture fuzzy uncertain linguistic set combining picture hesitant fuzzy set with uncertain linguistic term set is proposed. We firstly define the concepts of multi-valued picture fuzzy uncertain linguistic set and multi-valued picture fuzzy uncertain linguistic number. Hamacher operations are more general and flexible in information fusion, thus, Hamacher operations …and comparison method are developed at the same time. Improved generalized Heronian Mean operator can simultaneously reflect correlations between values and prevent the redundant calculation. Then, two operators of improved generalized weighted Heronian mean and improved generalized geometric weighted Heronian mean in view of Hamacher operations are proposed. Meanwhile, some distinguished properties and instances of two operators are explored as well. Moreover, a novel MCDM approach applying the developed operators is constructed. Ultimately, an illustrative example on vendor selection is performed, and sensitivity analysis and comparison analysis are provided to verify the powerfulness of the proposed method. Show more

Keywords: Hamacher, improved generalized heronian operator, multi-criteria decision-making, multi-valued picture fuzzy uncertain linguistic set

DOI: 10.3233/JIFS-210404

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1531-1552, 2021

Authors: Akram, Muhammad | Siddique, Saba | Ahmad, Uzma

Article Type: Research Article

Abstract: The main objective of this research article is to classify different types of m -polar fuzzy edges in an m -polar fuzzy graph by using the strength of connectedness between pairs of vertices. The identification of types of m -polar fuzzy edges, including α -strong m -polar fuzzy edges, β -strong m -polar fuzzy edges and δ -weak m -polar fuzzy edges proved to be very useful to completely determine the basic structure of m -polar fuzzy graph. We analyze types of m -polar fuzzy edges in strongest m -polar fuzzy path and m -polar fuzzy cycle. Further, we define …various terms, including m -polar fuzzy cut-vertex, m -polar fuzzy bridge, strength reducing set of vertices and strength reducing set of edges. We highlight the difference between edge disjoint m -polar fuzzy path and internally disjoint m -polar fuzzy path from one vertex to another vertex in an m -polar fuzzy graph. We define strong size of an m -polar fuzzy graph. We then present the most celebrated result due to Karl Menger for m -polar fuzzy graphs and illustrate the vertex version of Menger’s theorem to find out the strongest m -polar fuzzy paths between affected and non-affected cities of a country due to an earthquake. Moreover, we discuss an application of types of m -polar fuzzy edges to determine traffic-accidental zones in a road network. Finally, a comparative analysis of our research work with existing techniques is presented to prove its applicability and effectiveness. Show more

Keywords: α-strong m-polar fuzzy edges, β-strong m-polar fuzzy edges, Menger’s theorem for m-polar fuzzy graphs, Traffic-accidental zones in a road network, Flowchart

DOI: 10.3233/JIFS-210411

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1553-1574, 2021

Authors: Vaiyapuri, Thavavel | Alaskar, Haya | Sbai, Zohra | Devi, Shri

Article Type: Research Article

Abstract: Medical images that are acquired with reduced radiation exposure or following the administration of imaging agents with a low dose, are often known to experience problems by the noise stemming from acquisition hardware as well as psychological sources. This noise can adversely affect the quality of diagnosis, but also prevent practitioners from computing quantitative functional information. With a view to overcoming these challenges, the current paper puts forward optimization of multi-objective for denoising medical images within the wavelet domain. This proposed technique entails the use of genetic algorithm (GA) to get the threshold optimized within the denoising framework of wavelets. …Two purposes are associated with this technique: First, its ability to adapt with different noise types of noise in the image without requiring prior information about the imaging process per se. In addition, it balances relevant diagnostic details’ preservation against the reduction of noise by considering the optimization of the error factor of Liu and SNR as the foundation of objective function. According to the implementation of this method on magnetic resonance (MR) and ultrasound (US) images of the brain, a better performance has been observed as compared to the existing wavelet-based denoising methods with regard to quantitative and qualitative metrics. Show more

Keywords: Medical image denoising, rician noise, speckle noise, wavelet thresholding, threshold optimization, optimization techniques, multi-objective optimization

DOI: 10.3233/JIFS-210429

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1575-1588, 2021

Authors: Yin, Fangchen | Ji, Qinzhi | Jin, Chengwei | Wang, Jing

Article Type: Research Article

Abstract: Milling force prediction is one of the most important ways to improve the quality of products and stability in robot stone machining. In this paper, support vector machines (SVMs) are introduced to model the milling force of white marble, and the model parameters in the SVMs are optimized by the improved quantum-behaved particle swarm optimization (IQPSO) algorithm. A set of online inspection data from stone-machining robotic manipulators is adopted to train and test the model. The overall performance of the model is evaluated based on the decision coefficient (R2), mean absolute percentage error (MAPE) and root mean square error (RMSE), …and the results obtained by IQPSO-SVM are superior to those of the PSO-SVM model. On this basis, the relationship between the milling force of white marble and various machining parameters is explored to obtain optimal machining parameters. The proposed model provides a tool for the adjustment of machining parameters to ensure stable machining quality. This approach is a new method and concept for milling force control and optimization research in the robotic stone milling process. Show more

Keywords: Robot stone machining, quantum-behaved particle swarm algorithm, regression of support vector machines, milling force of white marble, machining parameters

DOI: 10.3233/JIFS-210430

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1589-1609, 2021

Authors: Dang, Xingyue | Liao, Shan | Cheng, Pengsen | Liu, Jiayong

Article Type: Research Article

Abstract: Recently, deep learning methods have been applied to deal with the opinion target extraction (OTE) task with fruitful achievements. On the other hand, since the features captured by the embedding layer can make a multiple-perspective analysis from a sentence, an embedding layer that can grasp the high-level semantics of the sentences is of essence for processing the OTE task and can improve the performance of model into a more efficient manner. However, most of the existing studies focused on the network structure rather than the significant embedded layer, which may be the fundamental reason for the problem of relatively poor …performance in this field, not mention the Chinese extraction model. To compensate these shortcomings, this paper proposes a model using multiple effective features and Bidirectional Encoder Representations from Transformers (BERT) on the architecture of Bidirectional Long Short-Term Memory (BiLSTM) and Conditional Random Field (CRF) for Chinese opinion target extraction task, namely MF-COTE, which can construct features from different perspectives to capture the context and local features of the sentences. Besides, to handle the difficult case of multiple nouns in one sentence, we innovatively propose noting words feature to regulate the model emphasize on the noun near the transition or contrast word, thus leading a better opinion target location. Moreover, to demonstrate the superiorities of the proposed model, extensive comparison experiments are systematically conducted compared with other existing state-of-the-art methods, with the F1-score of 90.76%, 92.10%, 89.63% on the Baidu, the Dianping, and the Mafengwo dataset, respectively. Show more

Keywords: Chinese opinion target extraction, multiple features, noting words, BERT, Long short-term memory

DOI: 10.3233/JIFS-210440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1611-1626, 2021

Authors: Garg, Harish | Ali, Zeeshan | Yang, Zaoli | Mahmood, Tahir | Aljahdali, Sultan

Article Type: Research Article

Abstract: The paper aims to present a concept of a Complex interval-valued q-rung orthopair uncertain linguistic set (CIVQROULS) and investigated their properties. In the presented set, the membership grades are considered in terms of the interval numbers under the complex domain while the linguistic features are added to address the uncertainties in the data. To further discuss more, we have presented the operation laws and score function for CIVQROULS. In addition to them, we present some averaging and geometric operators to aggregate the different pairs of the CIVQROULS. Some fundamental properties of the proposed operators are stated. Afterward, an algorithm for …solving the decision-making problems is addressed based on the proposed operator using the CIVQROULS features. The applicability of the algorithm is demonstrated through a case study related to brain tumors and their effectiveness is compared with the existing studies. Show more

Keywords: Aggregation operators, classifications of brain tumors, complex interval valued; q-rung orthopair uncertain linguistic sets

DOI: 10.3233/JIFS-210442

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1627-1656, 2021

Authors: Rodriguez, Luis | Castillo, Oscar | Garcia, Mario | Soria, Jose

Article Type: Research Article

Abstract: The main goal of this paper is to outline a new optimization algorithm based on String Theory, which is a relative new area of physics. The String Theory Algorithm (STA) is a nature-inspired meta-heuristic, which is based on studies about a theory stating that all the elemental particles that exist in the universe are strings, and the vibrations of these strings create all particles existing today. The newly proposed algorithm uses equations based on the laws of physics that are stated in String Theory. The main contribution in this proposed method is the new techniques that are devised in order …to generate potential solutions in optimization problems, and we are presenting a detailed explanation and the equations involved in the new algorithm in order to solve optimization problems. In this case, we evaluate this new proposed meta-heuristic with three cases. The first case is of 13 traditional benchmark mathematical functions and a comparison with three different meta-heuristics is presented. The three algorithms are: Flower Pollination Algorithm (FPA), Firefly Algorithm (FA) and Grey Wolf Optimizer (GWO). The second case is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting a statistical comparison of these results with respect to FA and GWO. In addition, we are presenting a third case, which is the optimization of a fuzzy inference system (FIS), specifically finding the optimal design of a fuzzy controller, where the main goal is to optimize the membership functions of the FIS. It is important to mention that we used these study cases in order to analyze the proposed meta-heuristic with: basic problems, complex problems and control problems. Finally, we present the performance, results and conclusions of the new proposed meta-heuristic. Show more

Keywords: New algorithm, stochastic process, performance, string theory, metaheuristics, control problem

DOI: 10.3233/JIFS-210459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1657-1675, 2021

Authors: Saeed, Muhammad | Ahsan, Muhammad | Ur Rahman, Atiqe | Saeed, Muhammad Haris | Mehmood, Asad

Article Type: Research Article

Abstract: Brain tumors are one of the leading causes of death around the globe. More than 10 million people fall prey to it every year. This paper aims to characterize the discussions related to the diagnosis of tumors with their related problems. After examining the side effects of tumors, it encases similar indications, and it is hard to distinguish the precise type of tumors with their seriousness. Since in practical assessment, the indeterminacy and falsity parts are frequently dismissed, and because of this issue, it is hard to notice the precision in the patient’s progress history and cannot foresee the period …of treatment. The Neutrosophic Hypersoft set (NHS) and the NHS mapping with its inverse mapping has been design to overcome this issue since it can deal with the parametric values of such disease in more detail considering the sub-parametric values; and their order and arrangement. These ideas are capable and essential to analyze the issue properly by interfacing it with scientific modeling. This investigation builds up a connection between symptoms and medicines, which diminishes the difficulty of the narrative. A table depending on a fuzzy interval between [0, 1] for the sorts of tumors is constructed. The calculation depends on NHS mapping to adequately recognize the disease and choose the best medication for each patient’s relating sickness. Finally, the generalized NHS mapping is presented, which will encourage a specialist to extricate the patient’s progress history and to foresee the time of treatment till the infection is relieved. Show more

Keywords: Tumor, neutrosophic hypersoft, mapping, inverse mapping

DOI: 10.3233/JIFS-210482

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1677-1699, 2021