Hybrid Dy-NFIS &amp; RLS equalization for ZCC code in optical-CDMA over multi-mode optical fiber

Ghazi, Alaan; Aljunid, S. A.; Idrus, Syed Zulkarnain Syed; Fareed, Alaa; Al-dawoodi, Aras; Hasan, Zahraa; Endut, R.; Ali, Noraziah; Mohsin, Aram Hewa; Abdullah, Sirwan Saber

doi:10.21533/pen.v9i1.1801

Cited by 4 publications

(2 citation statements)

References 43 publications

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“…As shown in Figure 2 , the proportion of the five multimodal sensory channels for accessing external information is 81%, 11%, 4.5%, 2.5%, and 1%, in that order. On the other hand, multimodality integrates multiple senses; that is, some neuroscience and brain science scholars have shown that the amount of information received by vision is much higher than that obtained by hearing [ 23 ]. The maximum amount of information the brain receives through the eyes per second is 100 Mbps.…”

Section: Multimodal Functionsmentioning

confidence: 99%

Research on the Multimodal Digital Teaching Quality Data Evaluation Model Based on Fuzzy BP Neural Network

Feng

2022

Computational Intelligence and Neuroscience

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We propose in this paper a fuzzy BP neural network model and DDAE-SVR deep neural network model to analyze multimodal digital teaching, establish a multimodal digital teaching quality data evaluation model based on a fuzzy BP neural network, and optimize the initial weights and thresholds of BP neural network by using adaptive variation genetic algorithm. Since the BP neural network is highly dependent on the initial weights and points, the improved genetic algorithm is used to optimize the initial weights and thresholds of the BP neural network, reduce the time for the BP neural network to find the importance and points that satisfy the training termination conditions, and improve the prediction accuracy and convergence speed of the neural network on the teaching quality evaluation results. The entropy value method, a data-based objectivity evaluation method, is introduced as the guidance mechanism of the BP neural network. The a priori guidance sample is obtained by the entropy method. Then, the adaptive variational genetic algorithm is used to optimize the BP neural network model to learn the a priori sample knowledge and establish the evaluation model, which reduces the subjectivity of the BP neural network learning sample. To better reflect and compare the effects of the two neural network evaluation models, BP and GA-BP, the sample data were continued to be input into the original GA and BSA to obtain the evaluation results and errors; then, the evaluation results of the two evaluation models, BP and GA-BP, were compared with the evaluation results of the two algorithms, GA and BSA. It was found that the GA-BP neural network evaluation model has higher accuracy and can be used for multimodal digital teaching quality evaluation, providing a more feasible solution.

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Section: Multimodal Functionsmentioning

confidence: 99%

Research on the Multimodal Digital Teaching Quality Data Evaluation Model Based on Fuzzy BP Neural Network

Feng

2022

Computational Intelligence and Neuroscience

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“…This reality contrasts with what is happening in Latin America, where a few initiatives have attempted to systematize the available information that conducted a bibliometric study on scientific production in environmental education; however, it is still pending to analyze the scientific activity on solid waste management [15]. Since in this continent, there is evidence of a large percentage of generation and very few initiatives for proper management [16], this despite having regulations for the comprehensive management of solid waste [17][18][19][20][21][22][23][24][25][26][27]. Therefore, the objective of this research was to analyze the Latin American scientific production on solid waste management in Scopus, period 2010 -2020.…”

Section: Introductionmentioning

confidence: 99%

Latin american production on solid waste management in scopus, 2010 - 2020

Tito-Betancur¹

2021

PEN

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Solid waste management has become a critical problem in developing countries, therefore, with the aim of analyzing the Latin American scientific production on solid waste management in Scopus, a retrospective descriptive study was conducted considering as the unit of analysis the publications on solid waste management in journals indexed in Scopus, during the period 2010 to 2020. The search included all published and indexed articles, using the fields Article Title, Abstracts, Keywords, having as search term the word "Solid waste management". As result, 494 articles were found, of which 420 are original, 58 are reviews, and the rest are letters, editorials, conference papers, and notes. Brazil stands out as the largest producer of solid waste management knowledge (62.5% of Latin American production), followed by Mexico, Colombia, Chile, and Argentina. On the other hand, 158 international institutions have participated in the Latin American production and only 10 have produced more than 10 articles, with universities in Brazil and Mexico standing out. Among the most productive journals, Waste Management and Waste Management And Research stand out; and the researchers with the most publications are Liséte Lange and Sandro Donnini Mancini. It is concluded that research on solid waste management in Latin America in the period 2010 -2020 is still deficient compared to other areas of the environmental field. The Latin American countries with the highest production in this area are Brazil, with more than 50%, followed by Mexico,

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