Matches in SemOpenAlex for { <https://semopenalex.org/work/W2131523816> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W2131523816 endingPage "1163" @default.
- W2131523816 startingPage "1155" @default.
- W2131523816 abstract "In the literature, many studies are conducted to obtain the mathematical models of semiconductor elements such as diodes, transistors, etc. These elements are commonly used in the circuits and systems. Main objective in this subject is to establish a mathematical model (or expression) to describe all the features of the semiconductor circuit elements. One of the most popular circuit elements is a diode. A general diode equation, which is commonly used in the solid-state physics literature, uses the diode leakage current, temperature values and material dependant coefficients other than the diode voltage. Major factor to get results as close as possible to actual results using this equation is to obtain the leakage current accurately. Otherwise, error in the results will be unacceptable. Therefore, in this study, a work has been carried out to obtain acceptable reverse saturation currents (or leakage currents) of a diode using three different methods, which are least squares, neural network and genetic algorithm. In addition, a new mathematical model of a semiconductor diode has been also proposed. This model is created using the actual measured diode current-voltage values. The new model is not using the diode leakage current, ambient temperature or coefficients of the diode construction materials. To obtain the diode characteristics using the above mentioned methods, a graphical user interface program has been also designed. The simulation/experimental results are obtained and compared using this program. By this way, validity of the proposed approximate model and other methods are proved. Key words: Diode, least square, neural network, genetic algorithm." @default.
- W2131523816 created "2016-06-24" @default.
- W2131523816 creator A5003164151 @default.
- W2131523816 creator A5020727141 @default.
- W2131523816 date "2010-05-31" @default.
- W2131523816 modified "2023-09-24" @default.
- W2131523816 title "Diode parameter extractions and comparisons using the least square method, neural networks and genetic algorithms" @default.
- W2131523816 cites W2002016471 @default.
- W2131523816 cites W2115123452 @default.
- W2131523816 cites W2146909695 @default.
- W2131523816 cites W2150714422 @default.
- W2131523816 cites W2891575902 @default.
- W2131523816 cites W2898916015 @default.
- W2131523816 cites W2951103780 @default.
- W2131523816 cites W3023540311 @default.
- W2131523816 doi "https://doi.org/10.5897/sre.9000360" @default.
- W2131523816 hasPublicationYear "2010" @default.
- W2131523816 type Work @default.
- W2131523816 sameAs 2131523816 @default.
- W2131523816 citedByCount "0" @default.
- W2131523816 crossrefType "journal-article" @default.
- W2131523816 hasAuthorship W2131523816A5003164151 @default.
- W2131523816 hasAuthorship W2131523816A5020727141 @default.
- W2131523816 hasConcept C11413529 @default.
- W2131523816 hasConcept C119599485 @default.
- W2131523816 hasConcept C119857082 @default.
- W2131523816 hasConcept C127413603 @default.
- W2131523816 hasConcept C134146338 @default.
- W2131523816 hasConcept C139719470 @default.
- W2131523816 hasConcept C155891486 @default.
- W2131523816 hasConcept C159985019 @default.
- W2131523816 hasConcept C162324750 @default.
- W2131523816 hasConcept C165801399 @default.
- W2131523816 hasConcept C178924924 @default.
- W2131523816 hasConcept C188855776 @default.
- W2131523816 hasConcept C192562407 @default.
- W2131523816 hasConcept C205200001 @default.
- W2131523816 hasConcept C23572009 @default.
- W2131523816 hasConcept C24326235 @default.
- W2131523816 hasConcept C2777042071 @default.
- W2131523816 hasConcept C2779227376 @default.
- W2131523816 hasConcept C41008148 @default.
- W2131523816 hasConcept C50644808 @default.
- W2131523816 hasConcept C78434282 @default.
- W2131523816 hasConcept C79635011 @default.
- W2131523816 hasConcept C8880873 @default.
- W2131523816 hasConceptScore W2131523816C11413529 @default.
- W2131523816 hasConceptScore W2131523816C119599485 @default.
- W2131523816 hasConceptScore W2131523816C119857082 @default.
- W2131523816 hasConceptScore W2131523816C127413603 @default.
- W2131523816 hasConceptScore W2131523816C134146338 @default.
- W2131523816 hasConceptScore W2131523816C139719470 @default.
- W2131523816 hasConceptScore W2131523816C155891486 @default.
- W2131523816 hasConceptScore W2131523816C159985019 @default.
- W2131523816 hasConceptScore W2131523816C162324750 @default.
- W2131523816 hasConceptScore W2131523816C165801399 @default.
- W2131523816 hasConceptScore W2131523816C178924924 @default.
- W2131523816 hasConceptScore W2131523816C188855776 @default.
- W2131523816 hasConceptScore W2131523816C192562407 @default.
- W2131523816 hasConceptScore W2131523816C205200001 @default.
- W2131523816 hasConceptScore W2131523816C23572009 @default.
- W2131523816 hasConceptScore W2131523816C24326235 @default.
- W2131523816 hasConceptScore W2131523816C2777042071 @default.
- W2131523816 hasConceptScore W2131523816C2779227376 @default.
- W2131523816 hasConceptScore W2131523816C41008148 @default.
- W2131523816 hasConceptScore W2131523816C50644808 @default.
- W2131523816 hasConceptScore W2131523816C78434282 @default.
- W2131523816 hasConceptScore W2131523816C79635011 @default.
- W2131523816 hasConceptScore W2131523816C8880873 @default.
- W2131523816 hasIssue "10" @default.
- W2131523816 hasLocation W21315238161 @default.
- W2131523816 hasOpenAccess W2131523816 @default.
- W2131523816 hasPrimaryLocation W21315238161 @default.
- W2131523816 hasRelatedWork W1971058262 @default.
- W2131523816 hasRelatedWork W1992281304 @default.
- W2131523816 hasRelatedWork W1996450453 @default.
- W2131523816 hasRelatedWork W2039513892 @default.
- W2131523816 hasRelatedWork W2070336810 @default.
- W2131523816 hasRelatedWork W2074460798 @default.
- W2131523816 hasRelatedWork W2106561770 @default.
- W2131523816 hasRelatedWork W2184553297 @default.
- W2131523816 hasRelatedWork W2187745983 @default.
- W2131523816 hasRelatedWork W2234907345 @default.
- W2131523816 hasRelatedWork W2291516760 @default.
- W2131523816 hasRelatedWork W2347435314 @default.
- W2131523816 hasRelatedWork W2419459359 @default.
- W2131523816 hasRelatedWork W2572193042 @default.
- W2131523816 hasRelatedWork W2766286512 @default.
- W2131523816 hasRelatedWork W2889343016 @default.
- W2131523816 hasRelatedWork W2896393250 @default.
- W2131523816 hasRelatedWork W2999106198 @default.
- W2131523816 hasRelatedWork W3011853359 @default.
- W2131523816 hasRelatedWork W3135888946 @default.
- W2131523816 hasVolume "5" @default.
- W2131523816 isParatext "false" @default.
- W2131523816 isRetracted "false" @default.
- W2131523816 magId "2131523816" @default.
- W2131523816 workType "article" @default.