Journal of Intelligent & Fuzzy Systems - Volume 41, issue 2

Authors: Zhang, Lingyun | Zhang, Pingjian

Article Type: Research Article

Abstract: Computational aesthetics, which uses computers to learn human aesthetic habits and ultimately replace humans in scoring images, has become a hot topic in recent years due to its wide application. Most of the initial research is to manually extract features and use classifiers such as support vector machines to score images. With the development of deep learning, traditional manual feature extraction methods are gradually replaced by convolutional neural networks to extract more comprehensive features. However, it is a huge challenge to artificially design an aesthetic neural network. Recently, Neural Architecture Search has upsurged to find suitable neural networks for many …tasks in deep learning. In this paper, we first attempt to combine Neural Architecture Search with computational aesthetics. We design and apply a customized progressive differentiable architecture search strategy to obtain a light-weighted and efficient aesthetic baseline model. In addition, we simulate the multi-person rating mechanism by outputting the distribution of the aesthetic value of the image, replacing the previous classification scheme of judging the beauty and unbeauty of the image by the threshold value, and propose a self-weighted Earth Mover’s Distance loss to better fit human subjective scoring. Based on the baseline model, we further introduce several strategies including an attention mechanism, the dilated convolution, and adaptive pooling, to enhance the performance. Finally, we design several groups of comparative experiments to demonstrate the effectiveness of our baseline aesthetic model and the introduced improvement strategies. Show more

Keywords: Artificial intelligence, deep learning, convolutional neural networks, computational aesthetics, neural architecture search

DOI: 10.3233/JIFS-210026

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2953-2967, 2021

Authors: Mohan, Prakash | Sundaram, Manikandan | Satpathy, Sambit | Das, Sanchali

Article Type: Research Article

Abstract: Techniques of data compression involve de-duplication of data that plays an important role in eliminating duplicate copies of information and has been widely employed in cloud storage to scale back the storage capacity and save information measure. A secure AES encryption de-duplication system for finding duplication with the meaning and store up it in the cloud. To protect the privacy of sensitive information whereas supporting de-duplication, The AES encryption technique and SHA-256 hashing algorithm have been utilized to encrypt the information before outsourcing. Pre-processing is completed and documents are compared and verified with the use of wordnet. Cosine similarity is …employed to see the similarity between both the documents and to perform this, a far economical VSM data structure is used. Wordnet hierarchical corpus is used to see syntax and semantics so that the identification of duplicates is done. NLTK provides a large vary of libraries and programs for symbolic and statistical natural language process (NLP) for the Python programming language that is used here for the unidentified words by cosine similarity. Within the previous strategies, cloud storage was used abundantly since similar files were allowed to store. By implementing our system, space for storing is reduced up to 85%. Since AES and SHA-256 are employed, it provides high security and efficiency. Show more

Keywords: Vector space Model, Wordnet, deduplication, cosine similarity, NLTK

DOI: 10.3233/JIFS-210038

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2969-2980, 2021

Authors: Zhang, Jin | Gu, Fu | Ji, Yangjian | Guo, Jianfeng

Article Type: Research Article

Abstract: To enable a quick and accurate access of targeted scientific and technological literature from massive stocks, here a deep content-based collaborative filtering method, namely DeepCCF, for personalized scientific and technological literature resources recommendation was proposed. By combining content-based filtering (CBF) and neural network-based collaborative filtering (NCF), the approach transforms the problem of scientific and technological literature recommendation into a binary classification task. Firstly, the word2vec is used to train the words embedding of the papers’ titles and abstracts. Secondly, an academic literature topic model is built using term frequency–inverse document frequency (TF-IDF) and word embedding. Thirdly, the search and view …history and published papers of researchers are utilized to construct the model that portrays the interests of researchers. Deep neural networks (DNNs) are then used to learn the nonlinear and complicated high-order interaction features between users and papers, and the top k recommendation list is generated by predicting the outputs of the model. The experimental results show that our proposed method can quickly and accurately capture the latent relations between the interests of researchers and the topics of paper, and be able to acquire the researchers’ preferences effectively as well. The proposed method has tremendous implications in personalized academic paper recommendation, to propel technological progress. Show more

Keywords: Scientific and technological literature resources, personalized recommendation, deep learning, recommendation algorithm

DOI: 10.3233/JIFS-210043

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2981-2996, 2021

Authors: Gao, Yin | Jia, Lifen

Article Type: Research Article

Abstract: Uncertain delay differential equations (UDDEs) charactered by Liu process can be employed to model an uncertain control system with a delay time. The stability of its solution always be a significant matter. At present, the stability in measure for UDDEs has been proposed and investigated based on the strong Lipschitz condition. In reality, the strong Lipschitz condition is so strictly and hardly applied to judge the stability in measure for UDDEs. For the sake of solving the above issue, the stability in measure based on new Lipschitz condition as a larger scale of applications is verified in this paper. In …other words, if it satisfies the strong Lipschitz condition, it must satisfy the new Lipschitz conditions. Conversely, it may not be established. An example is provided to show that it is stable in measure based on the new Lipschitz conditions, but it becomes invalid based on the strong Lipschitz condition. Moreover, a special class of UDDEs is verified to be stable in measure without any limited condition. Besides, some examples are investigated in this paper. Show more

Keywords: Stability in measure, Liu process, uncertain process, uncertain delay differential equations

DOI: 10.3233/JIFS-210089

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2997-3009, 2021

Authors: Senniappan, Gomathi | Umapathy, Prabha

Article Type: Research Article

Abstract:  Renewable energy presently occupies a prominent position in India’s overall energy generation scheme. In the midst of numerous alternative energy resources, solar energy is widely used as it persists in large volumes with varying specification ratings. It is suited for both stand-alone and grid-coupled application. The Maximum Power Tracking (MPPT) scheme has a profound effect on the operating efficiency of a Photovoltaic (PV) power plant. This paper proposes an inventive hybridized Human Psychology Optimization-Perturb and Observation (HPO-PO) MPPT approach for obtaining the optimal duty cycle of the boost converter to harvest global maxima from a grid-connected Total Cost Tied (TCT) …configured PV array of 4080 W. The suggested method provides enriched performance both in steady-state, as well as in rapid and randomly changing weather conditions. Comparison studies of various MPPT procedures, including Perturbation and Observation (PO), Artificial Bee Colony (ABC), and Human Psychology Optimization (HPO) in MATLAB environment, illustrate the usefulness of the evoked system in meeting its goals. The suggested MPPT procedure has offered enhanced activities in terms of voltage quality, maximum power tracking capability, and converter efficiency compared to other methods. The recommended hybridized MPPT approach is experimentally validated on a hardware set-up using a 16-bit dsPIC30F2010 Digital Signal Controller in enhancing the behavior of the grid-connected PV system. Show more

Keywords: Photovoltaic (PV) systems, MPPT, perturb and observation, artificial bee colony, human psychology optimization (HPO), hybrid HPO-PO

DOI: 10.3233/JIFS-210114

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3011-3030, 2021

Authors: Xiao, Yanjun | Zhang, Zhenpeng | Liu, Zhenhao | Zhang, Zonghua | Zhou, Wei | Liu, Weiling

Article Type: Research Article

Abstract: In textile machines, the stability of warp tension is one of the decisive factors for the reliability, stability and product quality of weaving process. In order to meet the improving requirement for weaving efficiency and fabric quality, it is proposed that a fuzzy optimization integral separation PID warp tension control scheme based on process sampling to improve the warp tension control level of loom. Aiming at the problems of time-varying, nonlinear and variable coupling in the warp tension control system of loom, the forming mechanism of warp tension is modeled and analyzed, and the sampling scheme of warp tension based …on process is proposed. Based on the periodic change of warp tension at macro level and continuous fluctuation at micro level, the integral separation control and fuzzy optimization theory are introduced to optimize the control effect of the control system on the basis of classical PID control algorithm. Finally, the simulation and experiment show that the scheme can improve the tension controls performance and effectively reduce the tension error fluctuation. Show more

Keywords: Rapier loom, tension control, closed loop control, fuzzy optimization, integral separation control

DOI: 10.3233/JIFS-210124

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3031-3044, 2021

Authors: El-Bably, M. K. | Abo-Tabl, E. A.

Article Type: Research Article

Abstract: The present work proposes new styles of rough sets by using different neighborhoods which are made from a general binary relation. The proposed approximations represent a generalization to Pawlak’s rough sets and some of its generalizations, where the accuracy of these approximations is enhanced significantly. Comparisons are obtained between the methods proposed and the previous ones. Moreover, we extend the notion of “nano-topology”, which have introduced by Thivagar and Richard [49 ], to any binary relation. Besides, to demonstrate the importance of the suggested approaches for deciding on an effective tool for diagnosing lung cancer diseases, we include a medical …application of lung cancer disease to identify the most risk factors for this disease and help the doctor in decision-making. Finally, two algorithms are given for decision-making problems. These algorithms are tested on hypothetical data for comparison with already existing methods. Show more

Keywords: Neighborhoods, topology, rough sets, generalized nano-topology, attributes reduction and lung cancer disease

DOI: 10.3233/JIFS-210167

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3045-3060, 2021

Authors: Wu, Hsien-Chung

Article Type: Research Article

Abstract: The main purpose of this paper is to establish a mechanical procedure to determine the membership functions using the data collected from the economic and engineering problems. Determining the membership functions from the collected data may depend on the subjective viewpoint of decision makers. The mechanical procedure proposed in this paper can get rid of the subjective bias of decision makers. The concept of solid families is also proposed by regarding the sets in a family to be continuously varied. The desired fuzzy sets will be generated in the sense that its α -level sets will be identical to the …sets of the original family. In order to achieve this purpose, any arbitrary families will be rearranged as the nested families by applying some suitable functions to the original families that are formulated from the collected data. Show more

Keywords: Nested families, non-normal fuzzy sets, solid families

DOI: 10.3233/JIFS-210201

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3061-3082, 2021

Authors: Ling, Jie | Xiong, Su | Luo, Yu

Article Type: Research Article

Abstract: Uniform Resource Location (URL) is the network unified resource location system that specifies the location and access method of resources on the Internet. At present, malicious URL has become one of the main means of network attack. How to detect malicious URL timely and accurately has become an engaging research topic. The recent proposed deep learning-based detection models can achieve high accuracy in simulations, but several problems are exposed when they are used in real applications. These models need a balanced labeled dataset for training, while collecting large numbers of the latest labeled URL samples is difficult due to the …rapid generation of URL in the real application environment. In addition, in most randomly collected datasets, the number of benign URL samples and malicious URL samples is extremely unbalanced, as malicious URL samples are often rare. This paper proposes a semi-supervised learning malicious URL detection method based on generative adversarial network (GAN) to solve the above two problems. By utilizing the unlabeled URLs for model training in a semi-supervised way, the requirement of large numbers of labeled samples is weakened. And the imbalance problem can be relieved with the synthetic malicious URL generated by adversarial learning. Experimental results show that the proposed method outperforms the classic SVM and LSTM based methods. Specially, the proposed method can obtain high accuracy with insufficient labeled samples and unbalanced dataset. e.g., the proposed method can achieve 87.8% /91.9% detection accuracy when the number of labeled samples is reduced to 20% /40% of that of conventional methods. Show more

Keywords: Malicious URL detection, network security, deep learning, semi-supervised learning

DOI: 10.3233/JIFS-210212

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3083-3092, 2021

Authors: Angelini, Pierpaolo | Maturo, Fabrizio

Article Type: Research Article

Abstract: This paper focuses on logical aspects of choices being made by the consumer under conditions of uncertainty or certainty. Such logical aspects are found out to be the same. Choices being made by the consumer that should maximize her subjective utility are decisions studied by revealed preference theory. A finite number of possible alternatives is considered. They are mutually exclusive propositions identifying all quantitative states of nature of a consumption plan. Each proposition of it is expressed by a real number. This research work distinguishes it from its temporary truth value depending on the state of information and knowledge of …the consumer. Since each point of the consumption space of the consumer belongs to a two-dimensional convex set, this article focuses on conjoint distributions of mass. Indeed, the consumption space of the consumer is generated by all coherent summaries of a conjoint distribution of mass. Each point of her consumption space is connected with a weighted average of states of nature of two consumption plans jointly studied. They give rise to a conjoint distribution of mass. The consumer chooses a point of a two-dimensional convex set representing that bundle of goods actually demanded by her inside of her consumption space. This paper innovatively shows that it is nothing but a bilinear and disaggregate measure. It is decomposed into two real numbers, where each real number is a linear measure. In this paper, different measures are obtained. They can be disaggregate or aggregate measures, where the latter are independent of the notion of ordered pair of consumption plans. Show more

Keywords: 2-parallelepiped, α-product, temporary truth value, antisymmetric tensor, non-linear metric, linear metric

DOI: 10.3233/JIFS-210234

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3093-3105, 2021