Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Wu, Mu-En | Lin, Sheng-Hao | Wang, Jia-Ching

Article Type: Research Article

Abstract: The objective in using the Kelly criterion for money management is to maximize returns; however, in many cases, the risk level exceeds that which the investor can bear. In this study, we present an algorithm to calculate the bidding fraction, while taking into account the level of risk (i.e., the maximum drawdown). The proposed algorithm is based on ensemble learning with a combination of bagging and subset resampling. Our assessment results obtained using the FF48 (i.e., Fama-French-48) dataset revealed that when the maximum drawdown was 5% and 10%, ensemble learning outperformed the conventional approach by 2% and 4%, respectively.

Keywords: Kelly criterion, ensemble learning, Monte Carlo simulation, money managemen

DOI: 10.3233/JIFS-179654

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Qu, Junsuo | Qiao, Ning | Shi, Haonan | Su, Chang | Razi, Abolfazl

Article Type: Research Article

Abstract: In this paper, we designed a smart bracelet to realize human behavior recognition, remote monitoring, fall detection, alarm and other functions. We use a six-axis inertial measurement module to collect a large amount of human body posture data. The Kalman filter is used to preprocess the data of acceleration and gyroscope, and then the processed series data is segmented by sliding window method. At last these data are put into a convolutional neural network(CNN) to identify human activities. Furthermore, we designed a two-level fall behavior judgment, the first-level threshold determination is performed through smart bracelet, when a suspected fall behavior …occurred, the sequence data are uploaded to the cloud platform, the second CNN discriminant model is triggered to accurately determine whether a fall behavior occurs. Show more

Keywords: Convolutional neural network, human behavior recognition, fall detection

DOI: 10.3233/JIFS-179651

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Xue, Xingsi | Wu, Xiaojing

Article Type: Research Article

Abstract:  Biomedical ontology matching dedicates to find two heterogeneous ontologies’ alignment and address their heterogeneity problem. Typically, a biomedical ontology has various biomedical concepts that are described with various labels and datatype property names, which forms a lexical space where each label or datatype property represents one dimension. Therefore, it is an effective way to present two biomedical concepts in a vector space, and use the cosine distance to measure their similarity. In this work, we present two biomedical concepts in a lexical vector space which is constructed with their inner and context concepts’ lexical information, and then utilize two vector’s …cosine distance to measure similarity value. Then, we propose a compact Evolutionary Algorithm (cEA) to find the concept correspondences. The experiment uses Ontology Alignment Evaluation Initiative (OAEI)’s testing cases, and the expeirmental results with Vector space Based Ontology Matcher (VBOM), Genetic Algorithm based Ontology Matcher (GAOM) and OAEI’s participants show the effectiveness of our proposal. Show more

Keywords: Biomedical ontology matching, lexical vector space, compact evolutionary algorithm

DOI: 10.3233/JIFS-179650

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2020

Authors: Li, Jingmei | Wu, Weifei | Xue, Di

Article Type: Research Article

Abstract:  Transfer learning is a new machine learning algorithm. It solves problems in different but related target domains by utilizing the knowledge in existing data. Based on the classical SVM algorithm and transfer learning, a selective transfer learning support vector machine (STL-SVM) algorithm is proposed in this paper. First, STL-SVM uses the maximum mean discrepancy to measure the weight vector of the source domain samples relative to the target domain, and selects samples from the source domain according to each weight to avoid negative transfer. Then, the knowledge in the source domain is learned by the approximate extreme point support vector …at the minimum training data cost. Finally, the object function is constructed by the obtained knowledge and the soft-margin SVM. In the constraint conditions of the objective function, the learned knowledge that is highly correlated with the target domain is selected, and further, the phenomenon of negative transfer is avoided in principle. STL-SVM solves the problem of negative transfer, and has considerable advantages in training time efficiency compared with the existing algorithms. The experimental results on artificial and real datasets show the effectiveness of the proposed algorithm. Show more

Keywords: Machine learning, support vector machine, transfer learning, classification

DOI: 10.3233/JIFS-190055

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2020

Authors: Wang, Xingang | Wang, Ke

Article Type: Research Article

Abstract: In many cases, complex problems cannot be accurately described by precise numerical values. Fuzzy theory provides a suitable tool for solving these problems. However, if decision makers cannot reach an agreement on the method for defining linguistic variables based on fuzzy sets, TIVFNs (triangular interval-valued fuzzy numbers) can provide more accurate modeling. Therefore, solving fuzzy MCGDM (multiple criteria group decision-making) problem with an unknown expert weight and criterion weight in TIVFNs has become an important research direction. In this paper, TIVF-VIKOR (triangular interval-valued fuzzy VIKOR) method, which is suitable for the environment of TIVFNs, is proposed to solve the problem …of fuzzy MCGDM. To achieve this goal, the TIVF-VIKOR method is innovatively adopted similarity and coefficient of variation are combined to calculate expert weight, and deviation maximization method based on divergence matrix is used to calculate criterion weight. VIKOR method is used to find the compromise solutions, which are converted into the form of binary connection number, and the optimal compromise solution is obtained after ranking. The proposed method is applied to the problem of machine fault detection, and the validity and feasibility of the method are illustrated. Compared with the TOPSIS∖ELECTRE method, the ranking results of the three methods are equivalent, and the fluctuation of the TIVF-VIKOR method is more distinct. Show more

Keywords: Triangular interval-valued fuzzy numbers, multiple criteria group decision-making, binary connection number, VIKOR method

DOI: 10.3233/JIFS-191261

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Liu, Yan | Wang, Xiao-Kang | Wang, Jian-Qiang | Li, Lin | Cheng, Peng-Fei

Article Type: Research Article

Abstract: This paper proposes a cloud model-based Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) method with 2D uncertain linguistic variables (2DULVs). 2DULVs are adopted by decision makers (DMs) to evaluate each alternative under the criteria because they can provide extra evaluation information. Cloud model is adopted to depict randomness and fuzziness. The possibility degree and possibility degree index are defined to develop an improved PROMETHEE II method for sorting alternatives. Entropy weight method is used to calculate the weight of each criterion. A renewable energy performance sample is used to illustrate the applicability of the proposed method. Sensitivity analysis and …four comparative experiments demonstrate the stability and accuracy of the proposed approach. Show more

Keywords: 2D uncertain linguistic variable, cloud, possibility degree, possibility degree index, improved PROMETHEE

DOI: 10.3233/JIFS-191546

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2020

Authors: Khater, Mostafa M.A. | Attia, Raghda A.M. | Qin, Haiyong | Kadry, Heba | Kharabsheh, R. | Lu, Dianchen

Article Type: Research Article

Abstract:  This research paper investigates the stable computational, semi-analytical, and numerical solutions of the nonlinear complex fractional generalized–Zakharov system. This system describes the nonlinear interactions between the low-frequency, acoustic waves and high-frequency, electromagnetic waves. The modified Khater method is applied to find the analytical solutions then the stability property of these solutions is discussed by using the Hamiltonian system properties. Moreover, stable computational solutions are used as the initial condition in the semi-analytical and numerical schemes. The Adomian decomposition and septic B–spline schemes are used to find the semi-analytical and numerical. For more explanation of the obtained analytical solutions, some sketched …are plotted in different types. Also, the comparison between the distinct types of obtained solutions is shown by calculating the absolute value of error. The performance of the used method explains the powerful, effective, and the ability for applying to different forms of nonlinear evolution equation. Show more

Keywords: The nonlinear complex fractional generalized–Zakharov system, modified Khater method, Adomian decomposition method, Septic B–spline scheme, computational, semi-analytical, and numerical solutions

DOI: 10.3233/JIFS-179569

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020

Authors: Shang, Bo | Huang, Taozhen | Du, Xingyu

Article Type: Research Article

Abstract: In a significant period of Chinese energy reformation to the point of expediting revolution in energy production and consumption, and promoting green low-carbon upgrading transformation of energy electricity, Chinese government has to implement the obligatory policy of renewable portfolio standards (RPS) with specific institutional provisions sternly. The renewable energy quotas in thermal power industry with carbon emission abatement constraints particularly have a latent impact on the behavior of thermal electricity producers, which is ineluctably involved in electricity connection of grid companies. To make clear the positive role in boosting investment in renewable energy generation in thermal power industry under mandatory …quotas requirements, we will utilize evolutionary game based on system dynamics (SD) to tackle with the sophisticated nexus among the government, thermal power producers and grid companies. We begin analysis of general evolutionary strategy stability in scenario ll by dynamically adjusting values of external variables of SD model to uncover pivotal variables affecting evolutionary strategy stability. Then in scenario I, the dynamic punishment structure consisting of cost elements to spark off the emulation of optimal manoeuvre selections of tripartite game agents is amended based on the simulation of vital variables affecting evolutionary strategy stability in scenario II. The significant conclusions provide decision-making support and management enlightenment for Chinese government to edge renewable energy generation capacity of thermal power producers and constrained degree of dynamic penalty for grid companies. Show more

Keywords: Renewable portfolio standards (RPS), China’s power market, Carbon abatement, Government regulation, evolutionary strategy stability, system dynamics

DOI: 10.3233/JIFS-191470

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-29, 2020

Authors: Mishra, Amit Kumar | Joshi, Nisheeth | Mathur, Iti

Article Type: Research Article

Abstract: Analysis of the terrorist network is a process to analyze or deriving Useful information from the available network data. Ranking The Terrorist nodes within a terrorist network in identifying the most influential node is essential for the elaboration of Covert network mining. The purpose of this paper is to implement an approach of two dimensional criteria weight determination along with logarithmic concept implementation for vital node investigation in term of their influential ability. Betweenness, Closeness, Eigenvector, Hub, In-degree, Inverse closeness, Out-degree and Total degree considered as criteria and terrorist involved in 9/11 terrorist attack considered as alternatives used to formulate …a decision problem. Although an integrated approach of Fuzzy based subjective-Aggregation concept based objective criteria weight determination and Ranking alternatives by the implementation of the logarithmic concept is used to solve multi criteria decision problems in order to show the application of most centralized node identification process which can be obtained easily by classification and selection problem solution using multiple criteria and alternatives. Show more

Keywords: Social network, Social Network Analysis(SNA), Terrorist network analysis(TNS), Fuzzy based criteria weight, Aggregation criteria weighting, Approach of logarithmic concept(APLOCO), Multi Criteria Decision Making(MCDN), Centrality measures, Most influential node

DOI: 10.3233/JIFS-191899

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: He, Sang-Sang | Wang, Yi-Ting | Wang, Jian-Qiang | Cheng, Peng-Fei | Li, Lin

Article Type: Research Article

Abstract: Failure mode and effect analysis is a powerful risk analysis tool in engineering management. When properly conducted, FMEA can make a huge contribution to reduce costs. The traditional FMEA ranks the failure modes on the basis of Risk Priority Number, which is defined as the multiplication of three risk factors. However, this method has always been criticized for it can’t handle the situation where the information given is uncertain or ambiguous. In order to extend the application of FMEA under the fuzzy environment, in this paper, we proposed a novel risk assessment model known as probabilistic linguistic ELECTRE II method …to rank failure modes based on FMEA. To realize this goal, probabilistic linguistic term sets (PLTSs) that consider both the hesitant information and probabilistic information are introduced to depict decision maker’s cognitive information. To better use the PLTSs in the decision-making process, some important information measures are defined, and a method to obtain the combined weight based on entropy weight of PLTSs is also proposed. Subsequently, we establish a score-deviation based PLTS-ELECTRE II model to study FMEA as a multi-criteria group decision-making problem. Finally, we successfully apply this model in a nuclear reheat valve system and the effectiveness of the proposed method is verified by sensitivity analysis and comparative analysis. Show more

Keywords: Risk management, outranking, probabilistic linguistic term set, combined weight, hybrid distance measure

DOI: 10.3233/JIFS-191398

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020