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ITHEA Classification Structure > K. Computing Milieux  > K.3 COMPUTERS AND EDUCATION  > K.3.2 Computer and Information Science Education
TRAINED NEURAL NETWORK CHARACTERIZING VARIABLES FOR PREDICTING ...
By: Sotto et al. (3710 reads)
Rating: (1.00/10)

Abstract: Many organic compounds cause an irreversible damage to human health and the ecosystem and are present in water resources. Among these hazard substances, phenolic compounds play an important role on the actual contamination. Utilization of membrane technology is increasing exponentially in drinking water production and waste water treatment. The removal of organic compounds by nanofiltration membranes is characterized not only by molecular sieving effects but also by membrane-solute interactions. Influence of the sieving parameters (molecular weight and molecular diameter) and the physicochemical interactions (dissociation constant and molecular hydrophobicity) on the membrane rejection of the organic solutes were studied. The molecular hydrophobicity is expressed as logarithm of octanol-water partition coefficient. This paper proposes a method used that can be used for symbolic knowledge extraction from a trained neural network, once they have been trained with the desired performance and is based on detect the more important variables in problems where exist multicolineality among the input variables.

Keywords: Neural Networks, Radial Basis Functions, Nanofiltration; Membranes; Retention.

ACM Classification Keywords: K.3.2 Learning (Knowledge acquisition)

Link:

TRAINED NEURAL NETWORK CHARACTERIZING VARIABLES FOR PREDICTING ORGANIC RETENTION BY NANOFILTRATION MEMBRANES

Arcadio Sotto, Ana Martinez, Angel Castellanos

http://foibg.com/ijita/vol16/IJITA16-3-p04.pdf

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K.3.2 Computer and Information Science Education
article: AUTOMATIZATION OF COMPUTER BUSINESS GAME AUTOMATON MODEL CONSTRUCTION · ONTOLOGY OF EDUCATIONAL STANDARDS · ALGORITHMS OF AUTOMATE MODEL CONSTRUCTION FOR BUSINESS GAME EXECUTION SUBSYSTEM · THE CONSTRUCTION OF COMPETENCY-BASED BUSINESS GAME OPERATIONAL MODEL · WAVELET TRANSFORM IN INVESTIGATIONS OF STUDENTS EDUCABILITY DEPENDENTLY ... · ALGORITHMS FOR GENERATING OPERATIONAL MODEL OF COMPETENCE BUSINESS GAMES · A MODEL FOR VISUAL LEARNING IN AUTISM · ON COMBINATION OF DEDUCTION AND ANALYTICAL TRANSFORMATIONS ... · TRAINED NEURAL NETWORK CHARACTERIZING VARIABLES FOR PREDICTING ... · TRAINED NEURAL NETWORK CHARACTERIZING VARIABLES ... · AN UML PROJECT OF A TASK-ORIENTED ENVIRONMENT FOR TEACHING ALGORITHMS · TQM IN E-LEARNING: A SELF-ASSESSMENT MODEL AND QUESTIONNAIRE · INFOSTATION-BASED ADAPTABLE PROVISION OF M-LEARNING SERVICES: ... · THE EXPERIENCE SOFTWARE-BASED DESIGN OF VIRTUAL MEDICAL ... · ABOUT THE EXPERIENCE OF DEVELOPING INTERACTIVE DYNAMIC ... · DOMAIN MODELING TO SUPPORT ANTI-CYBER CRIME EDUCATION · COGNITIVE APPROACH TO E-LEARNING IN SCIENCES AND TECHNOLOGIES ... · ALGORITHM OF CONSECUTIVE DEFINITION OF RANKING OF THE OBJECTS ... · ABOUT PROBLEMS OF DECISION MAKING IN SOCIAL AND ECONOMIC SYSTEMS · DEVELOPMENT OF EDUCATIONAL ONTOLOGY FOR C-PROGRAMMING · EDUCATIONAL MODEL OF COMPUTER AS A BASE FOR INFORMATICS LEARNING ·
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