Journal of Intelligent & Fuzzy Systems - Volume 39, issue 5

Authors: Tolga, A. Cagri | Basar, Murat

Article Type: Research Article

Abstract: Increasing population in the world drives people to find a different type of feeding regime. Even if there is an immense augmentation in crowd brilliant innovators are looking for new ways of farming more efficiently. Hydroponics is one of the novel paths that is a planting system without soil. The system reduces water usage by 95% and with the same rate provides efficiency in the crop, furthermore, sustainability is highly supplied. Traditional smart farming applied in the rural area strains immense transportation and brokership costs. In these days innovators make smart agriculture in vessel containers. Especially vertical and smart farming …made in the suburban area of the cities offers new opportunities on vegetables’ abundance. In this paper, the efficiency of this offered system is examined with minimizing the investment cost data. The system itself and the investment area have abounded with myriad uncertainties. Fuzzy logic tackles with those vaguenesses and fuzzy Evaluation Based on Distance from Average Solution (EDAS) method supplies assistance in the decision-making process of system evaluation. In addition, TODIM (a risk sensitive iterative multi-criteria decision making method based on Prospect Theory) is employed to check the evaluation of those three alternatives and to monitor how risk perception affects decision processes. A micro-based application is performed and attractive results are achieved. Show more

Keywords: Vertical urban agriculture, fuzzy EDAS method, fuzzy TODIM, investment cost, smart farming

DOI: 10.3233/JIFS-189100

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6325-6337, 2020

Authors: Çakır, Esra | Ulukan, Ziya

Article Type: Research Article

Abstract: Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power …plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem. Show more

Keywords: Project management, nearest interval approximation method, goal programming, fuzzy multi-objective linear programming, nuclear power plant

DOI: 10.3233/JIFS-189101

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6339-6350, 2020

Authors: Alcalde, Cristina | Burusco, Ana

Article Type: Research Article

Abstract: Information extracted from L-fuzzy contexts is substantially improved by taking into account different points of view, which can roughly be represented by criteria. This work addresses the general study of L-fuzzy contexts were a set of criteria is introduced, analyzing situations in which their evolution over time is known. The relationship among criteria is also an important point in the study. In this sense, the treatment will vary depending on whether they are independent criteria or there exists dependency among them. Of special importance will be those elements that stand out for presenting a positive temporal evolution. Four algorithms are …proposed in order to analyze the different situations. Finally, the applicability of the results is shown thought an example where the opinion of the clients of several hotels is analyzed taking into account both the type of traveler considered and the different aspects of the establishments on which a score is given. Show more

Keywords: L-fuzzy concept analysis, L-fuzzy context sequences, L-fuzzy contexts associated with criteria, WOWA operators, Choquet integrals

DOI: 10.3233/JIFS-189102

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6351-6362, 2020

Authors: Büyüközkan, Gülçin | Mukul, Esin

Article Type: Research Article

Abstract: Smart health applications are raising a growing interest around the world thanks to its potential to act proactively and solve health related problems with smart technologies. Smart health technologies can provide effective healthcare services such as personalization of treatments through big data, robotics in cure and care, artificial intelligence support to doctors, etc. The mixed structure of the evaluation of smart health technologies involves various contradictory criteria. However, when information is of uncertain nature, it is difficult to decide on how to treat. A hesitant fuzzy linguistic term set (HFLTS) approach is applied to overcome such uncertainties related to this …multi-criteria decision-making (MCDM) problem. This approach can be used to facilitate experts’ decision-making processes in complex and uncertain situations. In this study, an integrated hesitant fuzzy linguistic (HFL) MCDM approach is proposed to evaluate smart health technologies. The criteria are weighted with HFL Analytic Hierarchy Process (AHP), and then, smart health technologies are evaluated with the HFL Combinative Distance-based Assessment (CODAS) method. A comparative analysis with HFL COPRAS and HFL TOPSIS is applied. Lastly, the potential of this approach is presented through a case study. Show more

Keywords: Hesitant fuzzy linguistic term set, multi-criteria decision making, smart health, smart health technologies

DOI: 10.3233/JIFS-189103

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6363-6375, 2020

Authors: Barbara, Gładysz | Dorota, Kuchta

Article Type: Research Article

Abstract: The paper is based on a survey analyzing the success of IT projects in Poland as function of the cooperation with different stakeholders. The project’s participants expressed their subjective opinions on the effectiveness of the collective cooperation with various stakeholder groups. The impact of cooperation with different stakeholder groups: project team, management of the project implementation unit, suppliers and end users of the final product on the success of the project is examined. To this end, intuitionistic fuzzy sets, a correlation coefficient of intuitionistic fuzzy sets and an original method of intuitionistic fuzzy regression are applied. The conclusions point to …the most important stakeholder groups for the complete success and for the avoidance of a complete failure of IT projects. Some possibilities of the extension of the proposed method are indicated, so that the decision maker can adopt it to his or her preferences in searching for project success or failure factors. Show more

Keywords: IT Project Management, IT project success, project stakeholder, intuitionistic fuzzy set, intuitionistic correlation, intuitionistic regression

DOI: 10.3233/JIFS-189104

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6377-6389, 2020

Authors: Kalender, Zeynep Tugce | Kilic, Huseyin Selcuk | Tuzkaya, Gulfem | Dascioglu, Busra Gulnihan

Article Type: Research Article

Abstract: The prevalence of environmental studies in the academy has increased in recent years, depending on the adverse effects of global warming on natural resources. Besides various environmentally benign applications, one of the most important instruments on eliminating the negative environmental effects of an increasing population is electric vehicles. There are various topics within the concept of electric vehicles, including the determination of electric vehicle type, routing, network design, and so on. However, in this study, determining the locations of electric charging stations is the main focus. The problem is handled as a multi-criteria decision-making problem with the consideration of the …uncertainties in the decision-making environment. Specifically, the judgments of decision-makers play a critical role in the success of decisions, but for a decision-maker, it is usually difficult to express his/her preferences by using only one linguistic term due to the structure of some criteria type. Hence, with the proposed methodology, in this study, criteria are firstly classified as fuzzy and crisp according to their objective or subjective characteristics. Afterwards, besides the utilization of classic techniques for crisp type criteria, probabilistic linguistic terms sets are utilized for fuzzy type criteria with an extended version of TOPSIS. The proposed methodology is used for the comparison of 39 alternative electric charging locations in Istanbul, which is one of the most crowded cities in Europe. Show more

Keywords: Electric charging stations, plug-in electric vehicles, parking-lot-based charging location, TOPSIS, multi-criteria decision-making, probabilistic linguistic term sets

DOI: 10.3233/JIFS-189105

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6391-6406, 2020

Authors: Ilbahar, Esra | Cebi, Selcuk | Kahraman, Cengiz

Article Type: Research Article

Abstract: Effective utilization of renewable energy sources is an essential component of countries’ sustainable development strategies. A thorough evaluation of renewable energy alternatives is required to assure maximum exploitation of resources. The evaluation of renewable energy sources is a complicated problem since many criteria, even some of them are conflicting, must be taken into account simultaneously. Pythagorean fuzzy sets are better able to reflect uncertainty and vagueness in an assessment process by providing a greater domain for decision makers to describe their opinions. Therefore, this study aims at prioritizing renewable energy alternatives by employing interval-valued Pythagorean fuzzy WASPAS method. The obtained …results are compared to the results of intuitionistic type-2 fuzzy WASPAS, interval-valued intuitionistic fuzzy WASPAS and crisp WASPAS methods. Biomass is selected to be the best renewable energy alternative for Central Anatolia Region of Turkey. Show more

Keywords: Renewable energy evaluation, Pythagorean fuzzy sets, WASPAS

DOI: 10.3233/JIFS-189106

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6407-6417, 2020

Authors: Marcek, Dusan

Article Type: Research Article

Abstract: To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the …optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers. Show more

Keywords: ARIMA models, neural networks, learning algorithms, time series forecasting

DOI: 10.3233/JIFS-189107

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6419-6430, 2020

Authors: Haktanır, Elif

Article Type: Research Article

Abstract: Malcolm Baldrige National Quality Award (MBNQA) is a quality assessment and rewarding system that aims to increase the awareness of quality management. Although the award is launched in the USA in 1989 and only given to the U.S based companies, it is recognized internationally. There are 7 types of categories in the award system (Leadership, Strategic planning, Customer focus, Measurement, analysis, and knowledge management, Workforce focus, Process management, and Results) where the evaluation is made over 1000 points and each category has its own weight. Since almost all the publications in the literature are based on crisp measurements and evaluations …of the system performances, we proposed a multi attribute decision making (MADM) method using interval valued Pythagorean fuzzy weighted averaging (IVPFWA) and interval valued Pythagorean fuzzy weighted geometric (IVPFWG) aggregation operators for MBNQA assessment to represent the decision makers’ subjective evaluations better. A comparison of the results with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and an illustrative example are presented in the study. Show more

Keywords: Malcolm Baldrige National Quality Award, interval-valued Pythagorean fuzzy sets, multi attribute decision making, interval-valued Pythagorean fuzzy aggregation operators

DOI: 10.3233/JIFS-189108

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6431-6441, 2020

Authors: Piltan, Farzin | Prosvirin, Alexander E. | Kim, Jong-Myon

Article Type: Research Article

Abstract: Robotic manipulators represent a class of nonlinear and multiple-degrees-of-freedom robots that have pronounced coupling effects and can be used in various applications. The challenge of understanding complexity in a system’s dynamic behavior, coupling effects, and sources of uncertainty presents substantial challenges regarding fault estimation, detection, identification, and tolerant-control (FEDIT) in a robot manipulator. Thus, a proposed active fault-tolerant control algorithm, based on an adaptive modern sliding mode observer, is represented. Due to the effect of the system’s complexities and uncertainties for fault estimation, detection, and identification (FEDI), a sliding mode observer (SMO) is proposed. To address the sliding mode observer …drawbacks for FEDI such as high-frequency oscillation (chattering) and fault estimation accuracy, the modern (T-S fuzzy higher order) technique is represented. In addition, the adaptive technique is applied to the modern sliding mode observer (MSMO) to self-tune the coefficients of the fault estimation observer to increase the reliability and robustness of decision-making for diagnosis of the fault. Next, the residual delivered by the adaptive MSMO (AMSMO) is split into windows, and each window is characterized by a numerical parameter. Finally, the machine learning technique known as a decision tree adaptively derives the threshold values that are used for problems of fault detection and fault identification in this work. Due to control of the effective fault, a surface automated new sliding mode controller (SANSMC) is presented in this work. To address the challenge of chattering and unlimited uncertainties (faults), the AMSMO is applied to the sliding mode controller (SMC). In addition, the surface-automated technique is used to fine-tune the surface coefficient to reduce the chattering and faults in the robot manipulator. The results show that the machine learning-based automated robust hybrid observer significantly improves the robustness, reliability, and accuracy of FEDIT in unknown conditions. Show more

Keywords: Robot manipulator, sliding mode algorithm, observation technique, fuzzy logic technique, high-order sliding mode observer, adaptive technique, fault estimation, fault detection, fault identification, fault-tolerant control.

DOI: 10.3233/JIFS-189109

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6443-6463, 2020