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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Zhao, Hua | Zhang, PeiXin | Liang, Yue | Amos, Sitenda
Article Type: Research Article
Abstract: As a new research task, suggestion mining increasingly gained attention in recent years. However, it is still open and challenging due to complex semantics, large diversity of domains, and the absence of large labeled and balanced datasets. More importantly, most of the research is focused on English in-domain suggestion mining. But as compared to English, Chinese suggestion has more abundant expression forms, showing many different characteristics, so it is the necessity to carry out suggestions mining research in Chinese environment. In this work, the performances of several classification models for Chinese suggestion mining were compared. Firstly, a Chinese suggestion mining …corpus was constructed for open domain, and then trained several models for the suggestion mining, which included both traditional machine learning models (feature engineering-based models) and deep learning models. Our results demonstrated that these models can successfully classify Chinese sentences into two classes: suggestion and non-suggestion. The results of this study can guide future research in Chinese open domain suggestion mining. Show more
Keywords: Suggestion mining, Chinese open domain, Text classification
DOI: 10.3233/JIFS-211932
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5385-5398, 2022
Authors: Li, Shuailong | Zhang, Wei | Zhang, Huiwen | Zhang, Xin | Leng, Yuquan
Article Type: Research Article
Abstract: Model-free reinforcement learning methods have successfully been applied to practical applications such as decision-making problems in Atari games. However, these methods have inherent shortcomings, such as a high variance and low sample efficiency. To improve the policy performance and sample efficiency of model-free reinforcement learning, we propose proximal policy optimization with model-based methods (PPOMM), a fusion method of both model-based and model-free reinforcement learning. PPOMM not only considers the information of past experience but also the prediction information of the future state. PPOMM adds the information of the next state to the objective function of the proximal policy optimization (PPO) …algorithm through a model-based method. This method uses two components to optimize the policy: the error of PPO and the error of model-based reinforcement learning. We use the latter to optimize a latent transition model and predict the information of the next state. For most games, this method outperforms the state-of-the-art PPO algorithm when we evaluate across 49 Atari games in the Arcade Learning Environment (ALE). The experimental results show that PPOMM performs better or the same as the original algorithm in 33 games. Show more
Keywords: Model-based reinforcement learning, model-free reinforcement learning, policy optimization method
DOI: 10.3233/JIFS-211935
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5399-5410, 2022
Authors: Shabana Parveen, M. | Bhuvaneswari, P.T.V.
Article Type: Research Article
Abstract: Wireless Sensor Network (WSN) is a self-structured network containing small, energy-constrained wireless nodes that act together to accomplish difficult tasks. Wearable sensors, one of the WSNs play a significant role in healthcare applications, especially patient monitoring. With a miniature size, wearable sensors have less space dedicated for energy sources. So it is important for wearable sensors to be manufactured as energy efficient and reliable and it must ensure quality of service in providing the data. Remote health care monitoring has two limitations such as adoption of mobility and the usage of low power consumption devices. To overcome these limitations, appropriate …routing protocol can be used in Low Power Lossy Networks (LLNs). IPV6 Routing Protocol for Low Power Lossy Networks (RPL) is one of the routing protocols standardized to be applied in Internet of things network with wireless sensors. The current research article investigates the performance of RPL with three Objective Functions (OF), Minimum Rank with Hysteresis Objective Function (MRHOF) with Energy as metric, MRHOF with Expected Transmission count (ETX) as metrics and Objective Function zero(OF0) with hop count as metric, in elderly health care monitoring system. The study considered two scenarios case 1 has all static nodes while case 2 has few dynamic nodes. The performance was evaluated in terms of metrics control overhead, convergence time, Packet Delivery Ratio (PDR), Latency and energy consumption and the OF optimum for reliability, mobility and energy consumption is determined. The results of the simulation showed that, in mobile scenario OF0 converged at a fast rate than the MRHOF, which increases the life time. OF0 also consumed the least energy and it increased the life time of the node. As far as PDR is concerned, OF0 had low PDR when the nodes were mobile and ETX performed well. Show more
Keywords: RPL, health care, objective function, energy consumption, COOJA
DOI: 10.3233/JIFS-211943
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5411-5426, 2022
Authors: Ait Benali, B. | Mihi, S. | Ait Mlouk, A. | El Bazi, I. | Laachfoubi, N.
Article Type: Research Article
Abstract: Named Entity Recognition (NER) is a vitally important task of Natural Language Processing (NLP), which aims at finding named entities in natural language text and classifying them into predefined categories such as persons (PER), places (LOC), organizations (ORG), and so on. In the Arabic context, the current NER approaches based on deep learning are mainly based on word embedding or character-level embedding as input. However, using a single granularity representation has problems with out-of-vocabulary (OOV), word embedding errors, and relatively simple semantic content. This paper presents a multi-headed self-attention mechanism implemented in the BiLSTM-CRF neural network structure to recognize Arabic …named entities on social media using two embeddings. Unlike other state-of-the-art approaches, this approach combines character and word embedding at the embedding layer, and the attention mechanism calculates the similarity over the entire sequence of characters and captures local context information. The proposed approach better recognized NEs in Dialect Arabic, reaching an F1 value of 74.15% on Darwish’s dataset (a publicly available Arabic NER benchmark for social media). According to our knowledge, our findings outperform the current state-of-the-art models for Arabic Named Entity Recognition on social media. Show more
Keywords: Arabic named entity recognition (ANER), natural language processing (NLP), multi-head self-attention, BiLSTM, CRF, dialect arabic, social media
DOI: 10.3233/JIFS-211944
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5427-5436, 2022
Authors: Wang, Zeng | Liu, Weidong | Yang, Minglang
Article Type: Research Article
Abstract: As the main part of design display and evaluation, product three-dimensional (3D) form is the core object in affective product design. However, previous research has not yet addressed the development of technical models and method involving complete 3D surface data, and thus cannot guarantee the quality of affective product design. By using the techniques of triangular mesh model, spherical harmonic and conditional variational auto-encoder, this paper proposes a data-driven affective product design method composed of several technical models using complete 3D surface data. These models include: mathematical model for quantifying 3D form, recognition model for recognizing customer’s affective responses, and …generative model for generating new 3D forms. For affective product design, the mathematical model achieves the acquisition and processing of complete 3D surface data, the recognition model improves the objectivity and accuracy of recognition by integrating the 3D form data into the calculation process of emotion recognition, and the generative model realizes the automatic generation of new 3D forms in response to emotional data based on the recognition results. Each model provides technical support for realizing the acquisition, processing and generation of complete 3D surface data of product form, and ensures the systematicness and completeness of the proposed method for the affective product design involving 3D form innovation. The feasibility of the method is verified by an example of car design, and the results show that it is an effective affective product design method involving 3D form innovation. Show more
Keywords: Affective product form design, complete three-dimensional surface data, emotion recognition, spherical harmonic, conditional variational auto-encoder
DOI: 10.3233/JIFS-211947
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5437-5455, 2022
Authors: He, Peng | Zhou, Gang | Liu, Hongbo | Xia, Yi | Wang, Ling
Article Type: Research Article
Abstract: Knowledge Graph (KG) embedding approaches have been proved effective to infer new facts for a KG based on the existing ones–a problem known as KG completion. However, most of them have focused on static KGs, in fact, relational facts in KGs often show temporal dynamics, e.g., the fact (US, has president, Barack Obama, [2009–2017]) is only valid from 2009 to 2017. Therefore, utilizing available time information to develop temporal KG embedding models is an increasingly important problem. In this paper, we propose a new hyperplane-based time-aware KG embedding model for temporal KG completion. By employing the method of time-specific …hyperplanes, our model could explicitly incorporate time information in the entity-relation space to predict missing elements in the KG more effectively, especially temporal scopes for facts with missing time information. Moreover, in order to model and infer four important relation patterns including symmetry, antisymmetry, inversion and composition, we map facts happened at the same time into a polar coordinate system. During training procedure, a time-enhanced negative sampling strategy is proposed to get more effective negative samples. Experimental results on datasets extracted from real-world temporal KGs show that our model significantly outperforms existing state-of-the-art approaches for the KG completion task. Show more
Keywords: Temporal knowledge graph, knowledge graph completion, knowledge graph embedding
DOI: 10.3233/JIFS-211950
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5457-5469, 2022
Authors: Jahromi, Alireza Fakharzadeh | Hajiloei, Mehdi | Dehghani, Yeganeh | Lahoninezhad, Sara
Article Type: Research Article
Abstract: To overcome curse of dimensionality for outlier detecting in high dimensional dataset, axis-parallel subspace (SOD) and angle-based outlier detection (ABOD) methods were presented. These methods are also friendly used distance-based to detect outliers. In this regard, based on the reality of fuzzy data for explaining the world phenomena, this paper introduces an extended version of both methods for fuzzy dataset. First, the basic concepts of both methods are explained. Next we provide two metrics based on Euclidean and analytic distance to measure distance between fuzzy objects; also Cosine similarity measure formula for calculating the cosine of angle between two difference …vectors in high-dimensional fuzzy dataset is illustrated. Then the algorithms to determine outliers of fuzzy datasets by using these metrics and Cosine similarity measure, based on ABOD and SOD algorithms, are presented. Some numerical experimental examples are also presented, in which both real and synthesis datasets are used, For a real numerical examination, we have applied proposed algorithms to data from 15 Iranian petrochemical companies in a fully fuzzy environment. The obtained results show the significant properties of the new methods in detecting outliers. Show more
Keywords: Outlier detection, angle-based outlier detection, axis-parallel subspace, fuzzy number, cosine-similarity
DOI: 10.3233/JIFS-211955
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5471-5481, 2022
Authors: Yang, Hong | Wang, Fan | Gong, Zengtai
Article Type: Research Article
Abstract: Based on the granular derivative and the horizontal membership function of fuzzy-number-valued-function, the existence and uniqueness of solutions of two-point boundary value problem (BVP) for a class of second-order linear fuzzy ordinary differential equations are given, including the homogeneous BVP, the semi-homogeneous BVP and the non-homogeneous BVP. However, this is somewhat different from ordinary differential equations. In fact, we can think of it simply as the transformation from a number to a set, or we can think of it macroscopically as the transformation from a point to a plane. At the same time, appropriate examples are given to illustrate this …conclusion. Show more
Keywords: Fuzzy numbers, Fuzzy differential equations, Granular differentiability, The Horizontal membership function, Relative-distance-measure (RDM) fuzzy interval arithmetic
DOI: 10.3233/JIFS-211958
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5483-5499, 2022
Authors: Jin, Zhen-yu | Yan, Cong-hua
Article Type: Research Article
Abstract: The main purpose of this paper is to study initial and final Hutton type of linear fuzzifying uniformities. The detailed characterizations of initial and final linear fuzzifying uniformities are obtained. In addition, the boundedness, complete boundedness and T 2 separation axiom of initial linear fuzzifying uniform spaces are investigated. Some examples with respect to initial and final linear fuzzifying uniformities are also provided.
Keywords: Initial linear fuzzifying uniformities, final linear fuzzifying uniformities, boundedness, complete boundedness, T2 separation axiom
DOI: 10.3233/JIFS-211960
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5501-5509, 2022
Authors: Zhang, Zunhao | Zhang, Junxia | Tian, Wei | Li, Yang | Song, Yahui | Zeng, Qi
Article Type: Research Article
Abstract: The increasing market demand for milk powder has not only promoted the production capacity of milk powder, but also increased the impact on the environment. Therefore, it is very important to study the relationship between the environmental impact of milk powder spray drying (MPSD) system and system-related parameters and identify the key parameters to improve the efficiency of the sustainable improvement of the system. Treed Gaussian Process (TGP) and Standardized Regression Coefficients (SRC)methods are used to analyze the sensitivity of the system to environmental impacts. The results show that the inlet air temperature of the drying tower has the greatest …impact on the environment of the system, accounting for about 82%, followed by the atomization pressure and the feed pump speed, accounting for about 9% and 8% respectively. Moreover, not only the environmental performance of the system should be improved, but also the quality of milk powder should be guaranteed when optimizing the parameters such as the inlet air temperature of drying tower. This study can help the manufacturers of milk powder and related equipment to determine the priority of improving the system from the perspective of environmental protection. Show more
Keywords: Sensitivity analysis, treed Gaussian process, standardized regression coefficients, spray drying, environmental impact
DOI: 10.3233/JIFS-211961
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5511-5522, 2022
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