基于徑向基函數(shù)人工神經(jīng)網(wǎng)絡(luò)技術(shù)的東靈山遼東櫟林生物多樣性評(píng)價(jià)研究.pdf

1、東北林業(yè)大學(xué)碩士學(xué)位論文基于徑向基函數(shù)人工神經(jīng)網(wǎng)絡(luò)技術(shù)的東靈山遼東櫟林生物多樣性評(píng)價(jià)研究姓名：欒海燕申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：植物學(xué)指導(dǎo)教師：叢沛桐20030601AbstractForest，whosespeciesplaythecriticalroleinbiosphere，isthemainbodyoftheterrestrialecosystemDuetohistoricalreasonthatforestresourceshav

2、ebeenpersistentlyexploited，forestresourcesinChinaareundergoingincreasingpressure，thusfailtehabilitatenormallyNotonlythenumberofnaturalforestssharplydecreasesbutalsotheirqualitycontinuestodeclineForestecosystemisstillbein

3、gseriouslythreatenedsinceforestbiodiversityisevidentlydescendingandmanyspecificspeciesarefacingthefateofextinctionorevendisappearanceTherefore，forestbiodiversityconservationgreatlyinfluencestheecologicalenvironmentsinour

4、countryaswellasworldbiodiversityThevarianceregularityofQuercusliaotungensibiodiversityinDongLingMountainisanalyzedbytheaidofa&BindicesofspeciesdiversityaswellasRBFofartificialneuralnetworkinaccordancewiththeprinciplesofp

5、lantcommunitybiodiversityandnonlinearecologyinthisarticlewithQuercusliaotungensisinDonglingMountain，BeijingastheresearchobjectiveThechangesofBdiversityindicesofshrubandarborspeciesinQuercusliaotungensiarealsocomparedinth

6、earticleFunIIermore，thepredictiveevaluationtowardsthedevelopmentofbiodiversityofQuercusliaotungensishowsthat：aThechangingrangeisslightdespiteadiversityindicesofshrubandarbordiversityinQuercusliaotungensiatvariouselevatio

7、nsgraduallydecreasedThecompositionofcommunityspeciesisfavorabletosimplebindicesofarborandshrubdiversitiesinQuercusliaotungensiatvariOUSelevationsreflectthatarborspeciesandshrubspeciesdifferentlyinfluencethebiodiversityof

8、liaotungensiscQuerellsliaotungensiisastableforestasawholebecauseofitslowevolutionrateofspeciesandrelativelystablespeciescompositiondQNerczlsliaotungensiisthesingledominantcommunitywithcomplexenvironmentalheterogeneityapp

9、rovedbypredictiontowardsspatialheterogeneityofQuercusliaotungensisbiodiversitybyRBFaswellasevaluationoftherelationshipbetweengeographicalenvironmantalfactorsandbiodiversityeTheneuralnetworkmodeldesignedbyradialbasisfunct

10、ioninthisstudycallcalculateandsimulateregionalbiodiversityindicessoastoestablishthenonlinearrelationshipbetweenbiodiversityindicesandgeographicalenvironmentalfactorsunderanycircumstanceofgeographicalenvironmentsfRBF’asak

11、indofartificialneuralnetworkisaccessibletoevaluateandpredictforestbiodiversityandobjectivelyreflectstheactualstateofevaluatedforestsTheconclusionsofthestudymayofferthejnitialevidenceforevaluationofforestbiodiversityaswel