Journal of Intelligent & Fuzzy Systems - Volume 45, issue 1

Authors: Wajid, Mohd Anas | Zafar, Aasim | Terashima-Marín, Hugo | Wajid, Mohammad Saif

Article Type: Research Article

Abstract: Recent advances in technology and devices have caused a data explosion on the Internet and on our home PCs. This data is predominantly obtained in various modalities (text, image, video, etc.) and is essential for e-commerce websites. The products on these websites have both images and descriptions in text form, making them multimodal in nature. Earlier categorization and information retrieval methods focused mostly on a single modality. This study employs multimodal data for classification using neutrosophic fuzzy sets for uncertainty management for information retrieval tasks. This effort utilizes image and text data and, inspired by past techniques of embedding text …over an image, attempts to classify the images using neutrosophic classification algorithms. For classification tasks, Neutrosophic Convolutional Neural Networks (NCNNs) are used to learn feature representations of the produced images. We demonstrate how a pipeline based on NCNN can be utilized to learn representations of the innovative fusion method. Traditional convolutional neural networks are vulnerable to unknown noisy conditions in the test phase, and as a result, their performance for the classification of noisy data declines. Comparing our method against individual sources on two large-scale multi-modal categorization datasets yielded good results. In addition, we have compared our method to two well-known multi-modal fusion methodologies, namely early fusion and late fusion. Show more

Keywords: Multimodal data, early & late fusion, fuzzy logic, neutrosophic logic, convolutional neutral network

DOI: 10.3233/JIFS-223752

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1039-1055, 2023

Authors: Thao, Le Quang | Linh, Le Khanh | Thien, Nguyen Duy | Cuong, Duong Duc | Bach, Ngo Chi | Dang, Nguyen Ha Thai | Hieu, Nguyen Ha Minh | Minh, Nguyen Trieu Hoang | Diep, Nguyen Thi Bich

Article Type: Research Article

Abstract: The detection and prediction of cleaning conditions in school restrooms are crucial for reducing health risks and improving service quality. Traditional methods like manual hygienic inspection, fixed cleaning schedules, and automatic flushing devices have required large investments of money and effort from cleaning businesses to maintain cleanliness in school restrooms. To address this issue, we propose a prediction model based on Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) architecture. The model uses a dataset obtained from real-time conditions of the toilet via a wireless sensor network, enabling more efficient scheduling of toilet cleaning tasks. By predicting patterns of …Ammoniac (NH3) concentrations and Relative Humidity (RH) levels over time, our LSTM model is superior to the RNN model in performance, significantly reducing deviations in the NH3 and RH values with RMSE values of 3.32 and 2.85 , respectively. Furthermore, the model’s flexibility allows a variety of inputs to evaluate the need for cleaning at specific times, achieving maximum efficiency without requiring excessive neurons. Show more

Keywords: Wireless sensor network, manage clean restroom, LSTM, prediction

DOI: 10.3233/JIFS-230056

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1057-1065, 2023

Authors: Thao, Nguyen Xuan | Duong, Truong Thi Thuy

Article Type: Research Article

Abstract: Online reviews play a vital role in providing multidimensional information for tourists. It also has an effect on the ranking and overall score of hotels. As a powerful tool, the Fermatean fuzzy set efficiently models dealing with uncertain information. Considering that there is no study using the correlation coefficient in Fermatean fuzzy context to assess the effect of online reviews on ratings and overall score of hotels. Therefore, a correlation coefficient measure is put forward to determine the relationship between two Fermaten fuzzy numbers and then they are utilized to assess the impact of online reviews on ranking and overall …rating of hotels. The paper first introduces the TOPSIS–based ranking model using a new distance under Fermatean set. Then, we construct a new correlation coefficient between two Fermatean fuzzy numbers to measure the effect of online reviews with ranking, overall score and score of hotels under given criteria. A case study on TripAdvisor.com is performed to illustrate the proposed operator and model. Show more

Keywords: Hotels, decision making, picture fuzzy set, intuitionistic fuzzy set, Fermatean fuzzy set, correlation coefficient

DOI: 10.3233/JIFS-230667

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1067-1087, 2023

Authors: Babiyola, A. | Aruna, S. | Sumithra, S. | Buvaneswari, B.

Article Type: Research Article

Abstract: The need for a monitoring system has grown as a result of rising crime and anomalous activity. To avoid unusual incidents, the common man initiated video surveillance of important areas, which was then passed on to the government. In typical surveillance operations, surveillance devices create a vast volume of data that must be manually analysed. Manually handling huge data sets in real time results in information loss. To prevent abnormal incidents, the actions in sensitive areas can be properly monitored, evaluated, and alerted to the appropriate authorities. Previous deep learning-based activity identification methods have appeared, but the findings are inaccurate, …and the proposed Hybrid Machine Learning Algorithms (HMLA) incorporate two detection methods for surveillance videos like as Transfer Learning (TL) and Continual Learning (CL). As a result, the suspicious activity in the video may be missed. Consequently, numerous image processing and computer vision technologies were used in activity detection to decrease human effort and mistakes in surveillance operations. Activities in sensitive areas can be properly monitored and evaluated to avoid unusual incidents, and the appropriate authorities may be alerted. Hence, in order to decrease human error and effort in surveillance operations, activity recognition embraced a variety of image processing and computer vision technologies. In this present work, the capacity has constraints that impact recognition accuracy. Consequently, this research paper presents a HMLA based technique that uses feature extraction using multilayer (Long Short Term Memory) LSTM, Convolutional Neural Networks (CNN), and Temporal feature extraction using multilayer LSTM to improve identification accuracy by 96% while requiring minimal execution time. To show the superior performance of the proposed hybrid machine learning technique, a standard UCF crime dataset was utilised for experimental analysis and compared to existing deep learning algorithms. Show more

Keywords: Hybrid machine learning algorithms, surveillance videos, transfer learning, continual learning, recognition abnormal events

DOI: 10.3233/JIFS-231187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1089-1102, 2023

Authors: Deng, Wentao | Ma, Guoqing

Article Type: Research Article

Abstract: The quality evaluation of Chinese universities ideological and political (IAP) education has gone through the stages of defining tasks, proposing standards and exploring and carrying out, and has completed the stage tasks and accumulated practical experience. To construct the quality evaluation system of IAP education of Chinese universities in the new era, it is necessary to find the quality positioning in the fundamental task of establishing moral education and pay attention to the synergy between the internal and external parts of the quality of IAP education of Chinese universities. The IAP education quality evaluation of Chinese universities are the multiple-attribute …decision-making (MADM) issue. In this paper, we extend the geometric Heronian mean (GHM) operator to fuzzy number intuitionistic fuzzy numbers (FNIFNs) to propose the fuzzy number intuitionistic fuzzy weighted geometric HM (FNIFWGHM) operator. Then, the MADM method are built on FNIFWGHM operator. Finally, a numerical example for IAP education quality evaluation of Chinese universities and some comparative studies are used to prove the built methods’ credibility and reliability. Show more

Keywords: Multiple-attribute decision-making (MADM), Fuzzy number intuitionistic fuzzy numbers (FNIFNs), FNIFWHM operator, education quality evaluation

DOI: 10.3233/JIFS-224145

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1103-1118, 2023

Authors: Subha, K.J. | Rajavel, R. | Paulchamy, B.

Article Type: Research Article

Abstract: The Retinal image analysis has received significant attention from researchers due to the compelling need of early detection systems that aid in the screening and treatment of diseases. Several automated retinal disease detection studies are carried out as part of retinal image processing. Heren an Improved Ensemble Deep Learning (IEDL) model has been proposed to detect the various retinal diseases with a higher rate of accuracy, having multiclass classification on various stages of deep learning algorithms. This model incorporates deep learning algorithms which automatically extract the properties from training data, that lacks in traditional machine learning approaches. Here, Retinal Fundus …Multi-Disease Image Dataset (RFMiD) is considered for evaluation. First, image augmentation is performed for manipulating the existing images followed by upsampling and normalization. The proposed IEDL model then process the normalized images which is computationally intensive with several ensemble learning strategies like heterogeneous deep learning models, bagging through 5-fold cross-validation which consists of four deep learning models like ResNet, Bagging, DenseNet, EfficientNet and a stacked logistic regression for predicting purpose. The accuracy rate achieved by this method is 97.78%, with a specificity rate of 97.23%, sensitivity of 96.45%, precision of 96.45%, and recall of 94.23%. The model is capable of achieving a greater accuracy rate of 1.7% than the traditional machine learning methods. Show more

Keywords: Improved Ensemble Deep learning (IEDL), bagging through 5-fold cross-validation, Retinal Fundus Multi-Disease Image Dataset (RFMiD), Stacked logistic regression

DOI: 10.3233/JIFS-230912

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1119-1130, 2023

Authors: Yang, Xu

Article Type: Research Article

Abstract: The Petri net structure of workflow is used to model, and the moment generating function is used to analyze the time performance of workflow, and the complexity of analysis is given. It provides basic theory and basis for analysis and verification. The calculation of time complexity is given for sequence, concurrency, cycle, conflict (selection) and mutual exclusion. The performance analysis method based on moment generating function can be used to analyze the performance of arbitrarily distributed bounded or unbounded random Petri nets. Establish a broad-random Petri net model that conforms to the concept of workflow. Then, based on statistical analysis …and experience estimation of relevant data in the actual system, analyze the time nature of the on-demand service based on the analysis method based on behavioral expression, and obtain some valuable performance and index information. A necessary and sufficient condition for maintaining reliability of a workflow network model is given; A polynomial decomposition algorithm for P-invariants is proposed; Combining the moment function, a performance analysis method for workflow systems is established. An example is given to verify the effectiveness of the algorithm. Show more

Keywords: Performance analysis, workflow net, concurrent selection structure, read arcs, loop structure

DOI: 10.3233/JIFS-231137

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1131-1139, 2023

Authors: Al Ghour, Samer

Article Type: Research Article

Abstract: We use soft ω s -open sets to define soft ω s -irresoluteness, soft ω s -openness, and soft pre-ω s -openness as three new classes of soft mappings. We give several characterizations for each of them, specially via soft ω s -closure and soft ω s -interior soft operators. With the help of examples, we study several relationships regarding these three notions and their related known notions. In particular, we show that soft ω s -irresoluteness is strictly weaker than soft ω s -continuity, soft ω s -openness lies strictly …between soft openness and soft semi-openness, pre-ω s -openness is strictly weaker than ω s -openness, soft ω s -irresoluteness is independent of each of soft continuity and soft irresoluteness, soft pre-ω s -openness is independent of each of soft openness and soft pre-semi-openness, soft ω s -irresoluteness and soft continuity (resp. soft irresoluteness) are equivalent for soft mappings between soft locally countable (resp. soft anti-locally countable) soft topological spaces, and soft pre-ω s -openness and soft pre-semi-continuity are equivalent for soft mappings between soft locally countable soft topological spaces. Moreover, we study the relationship between our new concepts in soft topological spaces and their topological analog. Show more

Keywords: Soft ωs-open sets, soft ωs-continuous function, soft irresolute soft mapping, soft semi-open soft mapping, soft pre-semi-open soft mapping

DOI: 10.3233/JIFS-223332

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1141-1154, 2023

Authors: Tan, Guimei | Yu, Xichang

Article Type: Research Article

Abstract: As a powerful tool to model some unsharp concepts in real life, uncertain sets have been studied by more and more scholars. In order to characterize the degree of difficulty of uncertain sets, the hyperbolic entropy of an uncertain set and the hyperbolic relative entropy of uncertain sets are introduced in this paper. After that, this paper derived a key formula to calculate the hyperbolic entropy of an uncertain set via membership function, and some mathematical properties of hyperbolic entropy are also investigated in this paper. Finally, the hyperbolic entropy is applied in some research fields such as uncertain learning …curve, clustering of rare books and portfolio selection of collecting rare books. Show more

Keywords: Uncertainty theory, uncertain set, hyperbolic entropy, uncertain learning curve

DOI: 10.3233/JIFS-223626

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1155-1168, 2023

Authors: Xie, Wenxuan | Wu, Jiali | Sheng, Yuhong

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-223641

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1169-1178, 2023