Development of a Neuro-Fuzzy System for Assessing Information Management on the Shop Floor

Drigo, Edmara; Rodríguez, Jorge Laureano Moya; Embiruçu, Marcelo; Filho, Salvador Ávila

doi:10.1109/access.2020.3038061

Cited by 6 publications

(4 citation statements)

References 66 publications

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“…Foreign scholars also began to evaluate the development of e-commerce earlier [8]. Drigo et al analyzed the level of digital e-commerce in Singapore and emphasized the positive role of the government in establishing e-commerce infrastructure [9]. Luo et al investigated and analyzed e-commerce in nine underdeveloped countries with infrastructure problems [10].…”

Section: Introductionmentioning

confidence: 99%

Application of a Fuzzy Information Analysis and Evaluation Method in the Development of Regional Rural e-Commerce

Wang¹

2022

Advances in Multimedia

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As a new form of e-commerce, digital industry will become a tool to enhance regional competitiveness and win the allocation of resources, and its advanced degree is the standard to measure economic strength. In the process of development, countries and regions need to master their development status, so a set of digital industry evaluation index system is necessary to help various fields monitor the development status of e-commerce industry, aiming at providing more targeted services. Therefore, the establishment of regional digital industry progress index is conducive to evaluating and improving the development level of e-commerce. Because of the unbalanced development among different regions and the diversity and fuzziness of evaluation indexes, how to evaluate the development degree of cross-border electronic commerce in a region has become the main problem at present. In this paper, the evaluation index of regional promotion degree in cross-border electronic commerce is constructed, and on this basis, the intuitionistic fuzzy multiattribute group decision-making method based on induction is used to evaluate the promotion degree of regional cross-border electronic commerce. By analyzing the actual situation of cross-border Internet e-commerce comprehensive evaluation cases in various regions of Zhejiang Province, it is proved that this method is really effective. In view of this, this paper constructs an integrated multiangle monitoring index system of regional digital industry progress index, puts forward a subjective and objective method based on the principle of the minimum distance between the evaluated object and the ideal point, and combines the regional digital industry progress index with the comprehensive index method. The measurement model is used to measure the progress of digital industry in this region from June 2019 to June 2020, as an empirical object. The empirical results will show that this road is easy, and at the same time, we can fully grasp the progress of digital technology in a region.

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Section: Introductionmentioning

confidence: 99%

Application of a Fuzzy Information Analysis and Evaluation Method in the Development of Regional Rural e-Commerce

Wang¹

2022

Advances in Multimedia

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“…The combination of neural networks with other methods such as fuzzy logic, expert systems, genetic algorithms, wavelet analysis, chaos, coarse set theory, fractal theory, proof theory, and gray systems have been developed [75], [76]. Other techniques that adopted a combination of neurofuzzy algorithms have been successfully developed [77], [78], [79], [80], [81]. Aside of the neuro-fuzzy algorithms, neuro-genetic algorithm was also popularly used [82], [83], [84], [85], [86], [87], [88].…”

Section: Discussionmentioning

confidence: 99%

Current Trends in Intelligent Control Neural Networks for Thermal Processing (Foods): Systematic Literature Review

Marfuah

Ulya

Kusudaryati

et al. 2022

Journal of Robotics and Control

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Thermal processing is a technique for sterilizing foods through heating at high temperatures. Thermal processing plays a significant role in preserving foods economically, efficiently, reliably, and safely. Control in thermal processing of foods is necessary to avoid any decrease in food quality, i.e., color change, reduced content, sensory quality, and nutrition. Artificial Neural Network (ANN) has been developed as a computing method in research and developments on thermal processing methods to discover one suitable for food processing without damaging food quality. To this date, ANN has been used in food industries for modeling many processes. The paper aims to identify the latest trend in intelligent neural network control for the thermal processing of foods. The paper conducted a systematic literature review with five research questions using Preferred Reporting Items for Systematic Review (PRISMA). According to screening results and article selection, 240 potential articles have fulfilled the inclusion criteria. Then, each article was explored to identify the advantage and the advance of intelligent network control in thermal food processing. It can be concluded that the technology in information and computations of food processing has rapidly developed and advanced through the utilization of a combination of ANN with fuzzy logic and/or genetic algorithms.

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“…The application of computational intelligence-based tools has proven efficient in Engineering, Health Sciences, and Humanities, in studies that aim to evaluate subjective dynamics as well. Neuro-diffuse systems can be used to recognize patterns, functions, predictions, and control [75,76] The ANFIS is an intelligent system with the learning capability of neural network architecture. Thus, the ANFIS simultaneously processes linguistic variables and learns from the environment in which it is inserted.…”

Section: Anfis -Adaptative Neuro Fuzzy Systemmentioning

confidence: 99%

Development of Adaptive Neuro-Fuzzy Inference System for Assessing Industry Leadership in Accident Situations

et al. 2022

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Petroleum activity is characterized as a high-risk activity due to the probability of accidents with material and human losses. The leaders of this segment assume, besides the complex routine tasks, the challenge of making assertive decisions during an accident. This study aims to present an evaluation model of the Industry Leadership Index for Emergencies Situations (ILIE), using the Adaptive Neuro-Fuzzy System (ANFIS). The model was composed of 4 input variables, namely: knowledge, behavior, skill, and attitude; and one output variable, Industry Leadership. The data collection took place in petroleum production units in Brazil, with a sample of 151 respondents through the application of a survey. The observed data were treated in an Excel tabulator and used in the development of the ANFIS model. From this model, it was possible to carry out simulations to predict the impact, which the increase or decrease in the value of each input variable can influence the leader's profile. The model performed satisfactorily in the Root of the Mean Square Error (RMSE) analysis, being 0.199 in data training and 1.217 in data verification. The results suggest that the ANFIS method can be successfully applied to establish a model to analyze industry leaders prepared for assertive responses in crisis scenarios. .

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Development of a Neuro-Fuzzy System for Assessing Information Management on the Shop Floor

Cited by 6 publications

References 66 publications

Application of a Fuzzy Information Analysis and Evaluation Method in the Development of Regional Rural e-Commerce

Application of a Fuzzy Information Analysis and Evaluation Method in the Development of Regional Rural e-Commerce

Current Trends in Intelligent Control Neural Networks for Thermal Processing (Foods): Systematic Literature Review

Development of Adaptive Neuro-Fuzzy Inference System for Assessing Industry Leadership in Accident Situations

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