Journal of Intelligent & Fuzzy Systems - Volume 43, issue 6

Authors: Panjavongroj, Saruntorn | Phruksaphanrat, Busaba

Article Type: Research Article

Abstract: Enterprise Resource Planning (ERP) gives an organization a competitive edge by centralizing organization data and collaborating among supply chain networks. There are many types of software packages available, so most of the research proposed methods for prioritizing the best system. However, they did not suggest how to implement it, or which practices should be employed. So, this paper aims to propose a framework and a method for the selection of an ERP system and the best practice for implementation at the same time. A hybrid method of Logarithmic Fuzzy Preference Programming (LFPP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) is …presented for solving the problem. LFPP is reliable in obtaining weights, while DEMATEL can capture interrelationships between practices. It was applied to a case study supply chain network of a Thai automotive parts manufacturer to demonstrate the applicability; it could establish the priorities of criteria, rank alternatives, and select the appropriate practices at the same time. There is no study about software and practice selection by use of this proposed method before. The comparison of LFPP and the Fuzzy Full Consistency Method (FUCOM-F) was also performed. It shows that FUCOM-F uses a smaller number of pairwise comparisons than LFPP, but the obtained weights of LFPP are more consistent with the evaluation matrix than using FUCOM-F. Show more

Keywords: ERP system selection, logarithmic fuzzy preference programming (LFPP), decision-making trial and evaluation laboratory (DEMATEL), multiple attribute decision making, supply chain network

DOI: 10.3233/JIFS-221476

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7617-7631, 2022

Authors: Kiruba, D. Giji | Benitha, J.

Article Type: Research Article

Abstract: IoT-Mobile Wireless Sensor Networks (IMWSNs) are being employed in a variety of simulators to visually demonstrate the exposure, energy usage situation, and expected life duration of Internet of Things (IoT) mobile sensors. The majority of academics have projected and expanded routing procedures in order to extend the network’s life cycle. In IMWSNs, clustering is the most important process for improving energy efficiency. In cluster approaches, each IoT sensor node provides the acquired data to the cluster-head of their own cluster. The cluster-head embraces the conscientiousness of gathering prepared information and directing it to the arranged network’s basestation. A fuzzy based …energy proficient secure clustered routing (FEPSRC) is proposed in this research effort, which takes the residue energy, remoteness from the basestation, and compactness of IoT sensor nodes in its locality as input to the Fuzzy-Inference-System. For cluster-head selection, an eligibility ratio is calculated for each IoT sensor node. This protocol guarantees energy harmonizing by electing the preeminent IoT sensor node for the position of cluster-head, velocity of IoT sensor nodes are estimated and also provides best path for routing. The simulation consequence illustrates that projected fuzzy based energy proficient secure clustered routing condensed entire power expenditure, diminishes E-to-E delay, amplifies packet deliverance percentage and accomplishes maximal network life span. Show more

Keywords: Clustering, CH, energy effectiveness, fuzzy-logic, network life span

DOI: 10.3233/JIFS-212014

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7633-7645, 2022

Authors: Yousuff, Mohamed | Babu, Rajasekhara

Article Type: Research Article

Abstract: Melanoma, a kind of fatal skin cancer, originates in melanin secreting cells of the dermis. Disease identification in the early stages assures a high survival rate for the patient. Most of the existing techniques retard the cancer detection phase. Surface-Enhanced Raman Spectroscopy (SERS) can capture fine details from the specimens that machine learning models can utilize to discriminate between healthy and diseased individuals rapidly. Our research work proposes a deep autoencoder based hybrid dimensionality reduction approach with a machine learning model on SERS spectrums of human skin fibroblast for melanoma cancer diagnostics. SERS measurements of 307 samples in total, belonging …to two different classes, such as normal (157 samples) and malignant melanoma (150 samples), are used in this study. The SERS spectra measurements for both the samples lie between 100cm-1 and 4278cm-1 . The variations in the intensity of Raman bands between both classes are intrinsically subtle. Neighborhood Component Analysis (NCA) technique has been exerted to transform 2090 dimensional spectral features into 2090 dimensional vectors and then the Deep Autoencoder (DAE) model is used to handle the nonlinearity in the data and produce the latent space, while Linear Discriminant Analysis (LDA) classifier have been employed for discriminating the normal and cancer cells. The k-fold cross-validation technique with a k value of 10 is implemented to assess the metrics of the model. The stated hybrid (NCA and DAE) model with 10-dimension latent space achieves an accuracy of 98%, the sensitivity of 99% and specificity of 97%, respectively. Due to the high-intensity nature of the SERS spectrum, the existing linear dimensionality reduction based discriminating model fails if the class label (Normal or Cancer) gets distributed on the low variance side. The proposed methodology captures both linear and nonlinear underlying structures present in the spectrums, resulting in better classification compared to the standard dimensionality reduction techniques. Show more

Keywords: Dimensionality reduction, neighborhood component analysis, deep autoencoder, linear discriminant analysis, surface enhanced raman spectroscopy, melanoma

DOI: 10.3233/JIFS-212777

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7647-7661, 2022

Authors: Thilagavathy, A. | Mohanaselvi, S.

Article Type: Research Article

Abstract: In recent years, the extensions of fuzzy sets are much more familiar in almost all fields as they are reliable in defining the imprecise information of every decision-making situation. In this sequence of extensions, the cubical fuzzy sets are very efficient in dealing with imprecise information as it extends picture and spherical fuzzy sets. This article is interested in developing a new improved cubical fuzzy possibility degree measure. The desirable properties of the developed measure are also discussed. The advantage of the proposed measure is that it is capable of comparing the cubical fuzzy numbers in fuzzy nature itself and …provides the degrees of preference relations between them. A comparison study is made with the existing ranking measures to exhibit the feasibility and validity of the proposed approach. Based on the improved measure, a method for ranking cubical fuzzy numbers is constructed. A solution approach to a cubical fuzzy multiple attribute decision-making problem is presented. To exhibit the potency and the practical applicability of the proposal, two real-life instances of selecting the best-cutting fluid for cutting gears have been illustrated. The results are compared with the literature. Show more

Keywords: Cubical fuzzy set, cubical fuzzy number (CFN), possibility degree measure (PDM), improved possibility degree measure (IPDM), ranking

DOI: 10.3233/JIFS-220686

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7663-7678, 2022

Authors: Mahmood, Tahir | Ali, Zeeshan | Aslam, Muhammad | Chinram, Ronnason

Article Type: Research Article

Abstract: The major influence of this manuscript is to diagnose a valuable and considerable technique of Complex Picture Fuzzy Uncertain Linguistic setting and described its useful and valuable operational laws. The theory of Complex Picture Fuzzy Uncertain Linguistic information is massive modified and generalized than the Complex intuitionistic Fuzzy Uncertain Linguistic, Complex Fuzzy Uncertain Linguistic, Fuzzy Uncertain Linguistic and Uncertain Linguistic information. Keeping the supremacy and dominancy of the Complex Picture Fuzzy Uncertain Linguistic information, we investigated the Complex Picture Fuzzy Uncertain Linguistic Arithmetic Heronian Mean, Complex Picture Fuzzy Uncertain Linguistic Weighted Arithmetic Heronian Mean, Complex Picture Fuzzy Uncertain Linguistic Geometric …Heronian Mean and Complex Picture Fuzzy Uncertain Linguistic Weighted Geometric Heronian Mean operators. The property of idempotency, boundedness, monotonicity, and various well-known results with certain specific cases of the invented work are also deliberated. Furthermore, in the availability of the above-proposed analysis, we constructed a multi-attribute decision-making technique by considering the diagnosed operators for complex picture fuzzy uncertain linguistic information to enhance the worth and rationality of the invented theory. Finally, we illustrated the merits and restrictions of the novel operators by comparing them with certain prevailing operators based on fuzzy generalization. Finally, in the presence of evaluated examples, we compared the pioneered operators with various existing operators to enhance the feasibility and worth of the invented operators. Show more

Keywords: Complex picture fuzzy uncertain linguistic sets, arithmetic/geometric Heronian mean operators, decision-making methods

DOI: 10.3233/JIFS-221768

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7679-7716, 2022

Authors: Srinivas, Kachibhotla | Phani Kumar, Ch. Raghavendra

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-212857

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7717-7732, 2022

Authors: Shukla, Diksha | Chandra, Ganesh | Pandey, Babita | Dwivedi, Sanjay K.

Article Type: Research Article

Abstract: With the rise of social networks, people now express their sentiments more frequently and comfortably through their social media activities on different events, person, and every little thing surrounding them. This generates a lot of unstructured data; billions of users post tweets every day as a daily regime on Twitter itself. This has given rise to many texts classification and analysis tasks, Sentiment Analysis (SA) being one of them. Through SA, it is conferred whether the users have negative or positive orientations in their opinions; the results of this task are significantly useful for decision-makers in various fields. This paper …presents various facets of SA, like the process followed in SA, levels, approaches, and sentences considered in SA. Aspects such as growth, techniques, the share of various platforms, and SA pipeline are also covered in this paper. At last, we have highlighted some major challenges in order to define future directions. Show more

Keywords: Sentiment analysis, machine learning, lexicon based approach, hybrid approach

DOI: 10.3233/JIFS-213372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7733-7763, 2022

Authors: Liu, Fan | Luo, Muchen | Zhang, Yingyan | Zhou, Shuling | Wu, Xue | Lin, Aiyong | Guo, Yuxia | Liu, Conghu

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-220052

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7765-7778, 2022

Authors: Jarernsuk, Saran | Phruksaphanrat, Busaba

Article Type: Research Article

Abstract: Fuzzy multiple objective linear programming (FMOLP) approaches have been used to be solved many applications of multi-objective decision-making (MODM) problems. Several methods have been proposed including max-min approaches, preemptive approaches, and weighted approaches. However, they have some limitations in use; some may not be able to obtain efficient solutions or can give only a few solutions. Some methods need to be solved in two steps or specify the target level, which may be difficult for decision-makers (DMs). In this research, a new single-phase interactive fuzzy programming approach with priority control that can find several efficient solutions is proposed. It is …not necessary to specify the target value for each objective and it can solve with only one step for each solution. The DM can easily select the appropriate solutions from a set of efficient solutions. This method is different from existing single-phase approaches by controlling the satisfaction level of the last priority instead of using weight additive. Simple examples and a practical example of a perishable product supply chain network were tested to show the effectiveness of the proposed model. The performance of the proposed method was also compared with existing methods to verify and validate the model. Show more

Keywords: Fuzzy programming, multiple objective decision making, fuzzy-efficient solution, priority, perishable products supply chain network

DOI: 10.3233/JIFS-220367

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7779-7792, 2022

Authors: Zhang, Shanshan | Wei, Guiwu | Lin, Rui | Chen, Xudong

Article Type: Research Article

Abstract: The purpose of this paper is to provide an efficient multiple attribute group decision making (MAGDM) method to better serve the decision-makers(DMs), considering the real psychological state and preferences of the DMs when facing different risks. In real life, MAGDM is a very complex and uncertain problem, which needs to be considered from many aspects. In view of this, the intuitionistic fuzzy TOPSIS method on the basis of cumulative prospect theory (IF-CPT-TOPSIS) is proposed in this paper, which can effectively solve the above problems, cater to the expectations of DMs, and make the decision results more objective and more reliable. …The originality of this paper comes from three aspects. First, the new score function is combined with CRITIC method to calculate the weight of attributes, which eliminates the influence of Subjective preference of DMs and makes the primary information more reasonable. Furthermore, the use of the new score function can effectively avoid the exception conditions in the IFS problems. Secondly, applying the distance measurement formula of IFSs to determine the degree of approaching the ideal solution, so that the decision model can reflect the environmental changes more quickly. Thirdly, calculate the relative profit loss ratio of each scheme. Hence, each scheme is ranked and the optimal one is selected. Finally, in order to demonstrate the effectiveness of the model, a specific example is given and comparative analysis with the existing methods. The results show that the improved IF-CPT-TOPSIS method is useful and can be widely adapted for complex MAGDM problems. Show more

Keywords: Multiple attribute group decision making (MAGDM), intuitionistic fuzzy sets (IFSs), New score function, CRITIC method, IF-CPT-TOPSIS method

DOI: 10.3233/JIFS-220638

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7793-7806, 2022