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

Authors: Çağlıyor, Sandy | Öztayşi, Başar | Sezgin, Selime

Article Type: Research Article

Abstract: The motion picture industry is one of the largest industries worldwide and has significant importance in the global economy. Considering the high stakes and high risks in the industry, forecast models and decision support systems are gaining importance. Several attempts have been made to estimate the theatrical performance of a movie before or at the early stages of its release. Nevertheless, these models are mostly used for predicting domestic performances and the industry still struggles to predict box office performances in overseas markets. In this study, the aim is to design a forecast model using different machine learning algorithms to …estimate the theatrical success of US movies in Turkey. From various sources, a dataset of 1559 movies is constructed. Firstly, independent variables are grouped as pre-release, distributor type, and international distribution based on their characteristic. The number of attendances is discretized into three classes. Four popular machine learning algorithms, artificial neural networks, decision tree regression and gradient boosting tree and random forest are employed, and the impact of each group is observed by compared by the performance models. Then the number of target classes is increased into five and eight and results are compared with the previously developed models in the literature. Show more

Keywords: Machine learning algorithms, motion picture industry, forecasting

DOI: 10.3233/JIFS-189120

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6579-6590, 2020

Authors: Haktanır, Elif | Kahraman, Cengiz

Article Type: Research Article

Abstract: Failure mode and effects analysis (FMEA) is a structured approach for discovering possible failures that may occur in the design of a product or process. Since classical FMEA is not sufficient to represent the vagueness and impreciseness in human decisions and evaluations, many extensions of ordinary fuzzy sets such as hesitant fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, spherical fuzzy sets, and picture fuzzy sets. Classical FMEA has been handled to capture the uncertainty through these extensions. Neutrosophic sets is a different extension from the others handling the uncertainty parameters independently. A novel interval-valued neutrosophic FMEA method is developed …in this study. The proposed method is presented in several steps with its application to an automotive company in order to prioritize the potential causes of failures during the design process by considering multi-experts’ evaluations. Show more

Keywords: Failure mode and effect analysis, interval valued neutrosophic sets, risk priority number

DOI: 10.3233/JIFS-189121

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6591-6601, 2020

Authors: Yildiz, Didem | Temur, Gul T. | Beskese, Ahmet | Bozbura, F. Tunc

Article Type: Research Article

Abstract: In contemporary business life, retention of talented employees is crucial for organizations to preserve created value. Considering their attitudes, behaviors and personality, millenials are different from former generations, and retaining them requires a distinct management approach. This study aims to provide the decision makers with a more effective and efficient tool for evaluating career management activity types leading to employee retention of millenials. A novel method, Spherical Fuzzy Analytic Hierarchy Process (SFAHP) is used in the study to; (i) define the importance levels of the criteria having impact on employee retention, and (ii) assess various career management activity types for …employee retention. To ensure the practical use of the model, a numerical example from real world is presented. The results indicate that “leadership and management” is the most important factor, and “development-oriented career management activities” is the highest impact activity type in increasing the employee retention. Show more

Keywords: Employee retention, millenials, multi criteria decision making, spherical fuzzy sets, spherical fuzzy analytic hierarchy process, talent management

DOI: 10.3233/JIFS-189122

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6603-6618, 2020

Authors: Tekin, Ahmet Tezcan | Çebi, Ferhan

Article Type: Research Article

Abstract: Within the most productive route, online travel agencies (OTAs) intend to use advanced digital media ads to expand their piece of the industry as a whole. The metasearch engine platforms are among the most consistently used digital media environments by OTAs. Most OTAs offer day by day deals in metasearch engine platforms that are paying per click for each hotel to get reservations. The administration of offering methodologies is critical along these lines to reduce costs and increase revenue for online travel agencies. In this study, we tried to predict both the number of impressions and the regular Click-Through-Rate (CTR) …level of hotel advertising for each hotel and the daily sales amount. A significant commitment of our research is to use an extended dataset generated by integrating the most informative features implemented in various related studies as the rolling average for a different amount of day and shifted values for use in the proposed test stage for CTR, impression and sales prediction. The data is created in this study by one of Turkey’s largest OTA, and we are giving OTA’s a genuine application. The results at each prediction stage show that enriching the training data with the OTA-specific additional features, which are the most insightful and sliding window techniques, improves the prediction models ’ generalization capability, and tree-based boosting algorithms carry out the greatest results on this problem. Clustering the dataset according to its specifications also improves the results of the predictions. Show more

Keywords: CTR prediction, impression prediction, sales prediction, data enrichment, clustering, fuzzy clustering

DOI: 10.3233/JIFS-189123

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6619-6627, 2020

Authors: Kılıç, Hakan | Kabak, Özgür

Article Type: Research Article

Abstract: Human development and competitiveness have a causal relation. However, the literature is not clear on which one affects the other. This study investigates the bilateral relation between human development and competitiveness. For this purpose, initially, Fuzzy Analytic Network Process (FANP) is utilized to develop a composite index based on the relative importance weights of respective human development and competitiveness drivers. By FANP, the effects of key dimensions of human development and indexes of competitiveness on each other are taken into account. Subsequently, countries’ efficiencies on converting their human development to competitiveness and inversely, competitiveness to human development is measured by …Data Envelopment Analysis (DEA). Two different DEA models are developed to consider the bilateral relations. 45 countries are evaluated using both FANP and DEA models. Finally, the results are synthesized to reveal the direction of the relationship. It is found that the effect of competitiveness on human development is more significant than the effect of human development on competitiveness. Show more

Keywords: Human development, competitiveness of nations, fuzzy analytic network process, data envelopment analysis

DOI: 10.3233/JIFS-189124

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6629-6643, 2020

Authors: Dursun, Mehtap | Goker, Nazli | Mutlu, Hakan

Article Type: Research Article

Abstract: Organizations make use of project management methodologies, which provide an effective manner to achieve managerial goals, maintain the strength of the companies in increasing competition. Efficiency in planning, budgeting, and scheduling are provided so that high quality outputs are obtained through these processes. Agile project management methodology, which has been emerged from unpredictability of customer requirements and changeable business environment, is apt to cope with the failures of traditional project management tools. Besides, lean six-sigma project management methodology has become a combination of lean and six-sigma, which were opponent methodologies previously. This paper aims to determine the most suitable outsourcing …provider alternative by presenting a novel cognitive maps-based intuitionistic fuzzy decision making procedure. Interrelationships among evaluation criteria are weighted employing intuitionistic fuzzy cognitive map technique because of the causal links among evaluation criteria, vagueness, fuzziness, and hesitation in data. Moreover, the most appropriate provider alternative for both agile and lean six-sigma project management methodologies is identified by utilizing intuitionistic fuzzy TOPSIS method, which aims for minimizing the closeness to the ideal solution while maximizing the distance from the anti-ideal solution in hesitative environment. The case study is carried out in a bank that performs in Turkish banking sector. Show more

Keywords: Intuitionistic fuzzy sets, intuitionistic fuzzy cognitive map, IFTOPSIS, outsourcing provider selection, project management, agile, lean six-sigma

DOI: 10.3233/JIFS-189125

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6645-6655, 2020

Authors: Oner, Mahir | Ustundag, Alp

Article Type: Research Article

Abstract: Since information science and communication technologies had improved significantly, data volumes had expanded. As a result of that situation, advanced pre-processing and analysis of collected data became a crucial topic for extracting meaningful patterns hidden in the data. Therefore, traditional machine learning algorithms generally fail to gather satisfactory results when analyzing complex data. The main reason of this situation is the difficulty of capturing multiple characteristics of the high dimensional data. Within this scope, ensemble learning enables the integration of diversified single models to produce weak predictive results. The final combination is generally achieved by various voting schemes. On the …other hand, if a large amount of single models are utilized, voting mechanism cannot be able to combine these results. At this point, Deep Learning (DL) provides the combination of the ensemble results in a considerable time. Apart from previous studies, we determine various predictive models in order to forecast the outcome of two different case studies. Consequently, data cleaning and feature selection are conducted in advance and three predictive models are defined to be combined. DL based integration is applied substituted for voting mechanism. The weak predictive results are fused based on Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) using different parameters and datasets and best predictors are extracted. After that, different experimental combinations are evaluated for gathering better prediction results. For comparison, grouped individual results (clusters) with proper parameters are compared with DL based ensemble results. Show more

Keywords: Ensemble learning, deep neural networks, LSTM, deep ensemble learning

DOI: 10.3233/JIFS-189126

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6657-6668, 2020

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6669-6669, 2020

Authors: Barrón-Romero, César | Hernández-Zavala, Antonio

Article Type: Research Article

Abstract: Fuzzy processors are used for control actions in nonlinear mechatronic systems where high processing speed is required. The Field Programmable Gate Arrays (FPGA) are a good option to implement low cost fuzzy hardware in a short development time. A very important block in fuzzy hardware is the fuzzifier, since it affects directly in the accuracy of the result and in the processing time for obtaining a fuzzy number. There have been many design methodologies intended for enhancing the performance of this block. This paper presents a parallel fuzzifier circuit called α -BSSF. Its main design characteristics are the use of …α -levels for membership representation, usage of integer numbers, and avoiding time-consuming operations. As result, we obtained a fuzzifier that shows advantages in the reduction of the response time and computational resources against the existing sequential fuzzification methods. This proposal is targeted not only for T1FS, but also for T2FS, since the membership calculation through fuzzifier is applied in the same way but twice. Show more

Keywords: Digital Circuit design, Fuzzy hardware, Fuzzifier, FPGA, α - levels

DOI: 10.3233/JIFS-190291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6671-6685, 2020

Authors: Gao, Fei | Zhang, An | Bi, Wenhao

Article Type: Research Article

Abstract: Weapon system operational effectiveness evaluation is of significant importance to weapon system development, and it can be viewed as a multiple criteria decision-making problem with qualitative information, precise data, interval data, and even missing information. Furthermore, due to the complexity of weapon systems and military operations, using prior knowledge such as experiment data, simulation data, and experts’ knowledge could enhance the accuracy and reliability of the evaluation result. To this end, by introducing interval-valued evidential reasoning (ER) approach into belief rule-based system (BRBS), this paper proposed an interval-valued BRB inference method for weapon system operational effectiveness evaluation Firstly, the operational …effectiveness evaluation hierarchy is established based on the analysis of the weapon system. Then, the belief rule base (BRB) is constructed to capture prior knowledge of the weapon system. Next, different kinds of information are transformed into belief distribution, and the proposed interval-valued BRB inference method is applied to relay the input to the BRB and obtain the evaluation result. Finally, three numerical examples of missile system operational effectiveness evaluation with interval data, precise data, and missing information are conducted to illustrate the process of the proposed method and demonstrate its feasibility. Show more

Keywords: Weapon system, operational effectiveness evaluation, belief rule-based system, interval data, evidential reasoning approach

DOI: 10.3233/JIFS-190651

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6687-6701, 2020