Journal of Intelligent & Fuzzy Systems - Volume 43, issue 1

Authors: Khan, Rashid | Islam, M. Shujah | Kanwal, Khadija | Iqbal, Mansoor | Hossain, Md. Imran | Ye, Zhongfu

Article Type: Research Article

Abstract: Caption generation using an encoder-decoder approach has recently been extensively studied and implemented in various domains, including image captioning and code captioning. In this research article, we propose one particular approach for completing a capture generation task using an “attention”-based sequence-to-sequence framework that, when combined with a conventional encoder-decoder model, generates captions in an attention-based manner. ResNet-152 is a Convolutional Neural Network (CNN) based encoder that generates a comprehensive representation of an input image while embedding that into a fixed size length vector. To predict the next sentence, the decoder uses LSTM, a Recurrent Neural Network (RNN), and an attention-based …mechanism to concentrate attention on certain sections of an image selectively. Define a set of epochs to 69, which should be enough for training the model to generate informative descriptions, and the validation loss has reached its minimum limit and no longer decreases. We present the datasets as well as the evaluation metrics, as well as quantitative and qualitative analysis. Experiments on the MSCOCO and Flickr8k benchmark datasets illustrate the model’s efficacy in comparison to the baseline techniques. On MSCOCO, evaluation scores included BLEU-1 0.81, BLEU-2 0.61, BLEU-3 0.47, and 0.33 METEOR. For Flickr8k BLEU-1 0.68, BLEU-2 0.49, BLEU-3 0.41, METEOR 0.23, and 0.86 on SPICE. The proposed approach is comparable with several state-of-the-art methods in terms of standard evaluation metric, demonstrating that it can produce more accurate and richer captions. Show more

Keywords: Image captioning, CNN, LSTM, sequence-to-sequence, neural network

DOI: 10.3233/JIFS-211907

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 159-170, 2022

Authors: He, Yanping | Nan, TaiBen | Zhang, Haidong

Article Type: Research Article

Abstract: This paper is devoted to discussing the reverse triple I method based on the Pythagorean fuzzy set (PFS). We first propose the concepts of Pythagorean t-norm, Pythagorean t-conorm, residual Pythagorean fuzzy implication operator (RPFIO) and Pythagorean fuzzy biresiduum. The reverse triple I methods for Pythagorean fuzzy modus ponens (PFMP) and Pythagorean fuzzy modus tollens (PFMT) are also established. In addition, some interesting properties of the reverse triple I method of PFMP and PFMT inference models are analysed, including the robustness, continuity and reversibility. Finally, a practical problem is provided to illustrate the effectiveness of the reverse triple I method for …PFMP in decision-making problems. The advantages of the new method over existing methods are also expounded. Overall, compared with the existing methods, the proposed methods are based on logical reasoning rather than using aggregation operators, so the novel methods are more logical, can better deal with the uncertain problems in complex decision-making environments and can completely reflect the decision-making opinions of decision-makers. Show more

Keywords: Reverse triple I method, PFS, RPFIO, robustness, continuity

DOI: 10.3233/JIFS-211994

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 171-186, 2022

Authors: Liu, Hongping | Ge, Qian | Wei, Ruiju

Article Type: Research Article

Abstract: This paper aims to further study the new kind of ordered fuzzy group named ordered L -group, which is put forward in literature [20 ]. Some algebraic properties of ordered L -groups, such as the relationship between elements, the equivalent characterizations and the products of these groups are discussed. Following that, the properties of substructures including characterization theorems, the convexity, the products of (normal) subgroups maintain the original substructure, along with the properties of ordered L -group homomorphisms are explored. The discussion of ordered fuzzy groups in this paper is from the perspective of fuzzy binary operation, which is different …from the commonly method that just discuss the fuzzification of substructures in the research of fuzzy algebra. It can better reflect the essence of fuzzy groups logically just like that of classical groups. Show more

Keywords: L-poset, ordered L-operation, ordered L-group, convex structure, subgroup

DOI: 10.3233/JIFS-212027

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 187-199, 2022

Authors: Xiao, Yuanyuan | Zhang, Xiuguo | Xu, Xuemin | Cao, Zhiying

Article Type: Research Article

Abstract: Internet of Things (IoT) services are directly deployed on resource-constrained smart devices. Smart devices are characteristic by spatial and temporal constraints and energy limitations. A single IoT service cannot meet the complex requirements of users, so multiple IoT services need to be combined to provide services to users. As more and more smart devices are deployed in IoT, how to select IoT services with lower energy consumption and better quality of service (QoS) for service composition becomes a challenging problem. Combined with the characteristics that the data information of IoT is closely related to geographical location, the GeoHash algorithm is …used to locally screen services based on geographical location, so as to narrow the range of candidate services. For smart devices with energy constraints, this paper proposes a combined optimization model. The model considers not only the transmission energy consumption and switching energy consumption, but also the execution energy consumption when the device provides services. In order to balance QoS attributes and energy consumption, the composition problem is regarded as a multi-objective optimization problem and solved using a genetic algorithm (GA). The simulation results show that service composition scheme selected by this service composition optimization model has lower energy consumption and higher service quality. Show more

Keywords: Energy consumption, QoS, service composition optimization model

DOI: 10.3233/JIFS-212033

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 201-218, 2022

Authors: Wang, Pei | Qu, Liangdong | Zhang, Qinli

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-212037

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 219-236, 2022

Authors: Wu, Meiqin | Wang, Xinsheng | Fan, Jianping

Article Type: Research Article

Abstract: Three-way decisions (TWDs) theory is one of the core ideas of decision-theoretic rough sets (DTRSs). Reviewing the existing research results, we find that TWDs provides us with more flexible decision choices. And the traditional fuzzy number does not take into account the absence of information (indifference) in the evaluation process. In order to construct a new model which can get flexible decision results in complex decision environment, we introduce four-branch fuzzy numbers (FBFNs) to describe the evaluation information, so that the decision-makers can express the evaluation information more comprehensively. In this paper, a novel TWDs model in four-branch fuzzy environment …is proposed to solve multiple-attribute decision-making (MADM) problem. The first challenge is to construct a TWDs model based on FBFNs and to develop a new linguistic interpretation of the loss functions. Then, we extend a method for aggregating the loss functions obtained from the attribute evaluation values. Finally, we use the nonlinear solution to solve the threshold, and apply TOPSIS method to solve the conditional probability of FBFNs. The effectiveness of this method is illustrated by an example, and the decision results are compared with a MADM method based on OWGA operator. Show more

Keywords: Three-way decisions, four-branch fuzzy numbers, multiple-attribute decision-making, loss function, nonlinear solution, TOPSIS

DOI: 10.3233/JIFS-212097

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 237-248, 2022

Authors: Javanmardi, Ehsan | Nadaffard, Ahmadreza | Karimi, Negar | Feylizadeh, Mohammad Reza | Javanmardi, Sadaf

Article Type: Research Article

Abstract: In this research, a timely diagnosis and prediction mechanism for drill failure are provided to improve the maintenance process in drilling through fuzzy inference systems. Failures and decisions are based on information and reliability as well, and that affects the quality of decision-making. We apply the potential of if-then rules and a new approach called Z-number that considers fuzzy constraints and reliability at the same time. Exerting Z-number in this research took maximum advantage of reducing uncertainty for predicting failures. Additionally, this research has a practical aspect in maintenance systems by using if-then rules that rely on Z-number. The proposed …approach can cover the expert idea during drill operation time simultaneously. This approach also helps experts encounter ambiguous situations and formulate uncertainties. Experts or drill operators can consider key factors of drilling collapse along with the reliability of these factors. The proposed approach can be applied to a real-life situation of human inference with probability for the purpose of predicting failures during drilling. Hence, this method has excellent flexibility for implementation in various maintenance systems. Show more

Keywords: Maintenance, fuzzy inference, fuzzy logic, Z-number

DOI: 10.3233/JIFS-212116

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 249-263, 2022

Authors: Wu, Rong | Lin, Yidong

Article Type: Research Article

Abstract: As an important mathematical theory in intelligent learning and assessment system, knowledge space theory merely cares about items are mastered or non-mastered. Thus it needs to be further explored to achieve more precise and interpretable analysis. To this end, this paper mainly focuses on knowledge structures in corporate with Solo taxonomy. Then, fuzzy knowledge structure and fuzzy learning space are gradually developed. The corresponding knowledge base and surmise relation are explored respectively as well. In such case, the induced maximal knowledge space and its properties are further studied sufficiently. And three kinds of skill models are put forward based on …skill proficiency. Finally, a case study is presented to illustrate the advantage in learning description. Show more

Keywords: Base, fuzzy knowledge state, surmise systems, skill proficiency

DOI: 10.3233/JIFS-212176

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 265-278, 2022

Authors: Zhang, Tingting | Tang, Zhenpeng | Zhan, Linjie | Du, Xiaoxu | Chen, Kaijie

Article Type: Research Article

Abstract: An important feature of the outbreak of systemic financial risk is that the linkage and contagion of risk amongst the various sub-markets of the financial system have increased significantly. In addition, research on the prediction of systemic financial risk plays a significant role in the sustainable development of the financial market. Therefore, this paper takes China’s financial market as its research object, considers the risks co-activity among major financial sub-markets, and constructs a financial composite indicator of systemic stress (CISS) for China, describing its financial systemic stress based on 12 basic indicators selected from the money market, bond market, stock …market, and foreign exchange market. Furthermore, drawing on the decomposition and integration technology in the TEI@I complex system research methodology, this paper introduces advanced variational mode decomposition (VMD) technology and extreme learning machine (ELM) algorithms, constructing the VMD-DE-ELM hybrid model to predict the systemic risk of China’s financial market. According to eRMSE , eMAE , and eMAPE , the prediction model’s multistep-ahead forecasting effect is evaluated. The empirical results show that the China’s financial CISS constructed in this paper can effectively identify all kinds of risk events in the sample range. The results of a robustness test show that the overall trend of China’s financial CISS and its ability to identify risk events are not affected by parameter selection and have good robustness. In addition, compared with the benchmark model, the VMD-DE-ELM hybrid model constructed in this paper shows superior predictive ability for systemic financial risk. Show more

Keywords: Systemic financial risk, financial stress indicator, artificial intelligence model, VMD, DE-ELM

DOI: 10.3233/JIFS-212178

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 279-294, 2022

Authors: Luo, Huiyin | Jiang, Feng | Lin, Hongyu | Yao, Jian | Liu, Jiaxin | Jiang, Yu | Ren, Jia

Article Type: Research Article

Abstract: Monitoring the diversity of wild animals is a core part of the research and protection of wild animals. Due to the harsh outdoor environment, researchers cannot squat in the deep forest for a long time. Therefore, designing a sensor network system for wildlife monitoring is of great value to wildlife research, protection, and management. When deploying a wildlife monitoring network in the wild environment, it is necessary to solve the problem of the effective use of energy. To this end, this paper proposes an energy-saving optimization method for node scheduling and a wake-up scheme based on a cultural genetic algorithm. …This method achieves the purpose of energy saving by making redundant nodes fall asleep and waking up sleep nodes to repair the coverage blind area caused by dead nodes. Simulation results show that this method can activate fewer sensor nodes to monitor the required sensing area, and its performance is better than other known solutions. Show more

Keywords: Cultural genetic algorithm, wild animal monitoring, wireless sensor network, coverage control, energy saving

DOI: 10.3233/JIFS-212187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 295-307, 2022