水华论文翻译终稿.doc

水华论文翻译终稿 （1）Assuming thatwe ignorethe suddenbad weatherlike hurricaneaffection towardswaterblooms （2）Assuming that the chlorophyll a concentration is the only standardto measurethe water level. （3）Assuming thatweuseone weekas theunit timetopredictblooms our.2.2The provisionsof thesymbols andinstructions SymbolsProvisions TNTotal nitrogenTP TotalPhosphorus SDWater TransparencyWT WaterTemperature DODissolved OxygenC Chlorophylla JTransition layer node numberm Input layer nodesnumber nOutput layernode number()ix kK input sample()id kK outputsample()hhi k、()hyi kEachnode inputtransition layer()hho k、()hyo kEachnode outputtransition layer()o kPartial derivative of theerror functiontothenode of theoutputlayer()h kThe output of the transition layercalculationerror function for thepartialderivativeof transition layer neurons()how kconnecting weightvalues.E GlobalError3.Analysis and solutionoftask one3.1Analysis oftask oneWe arerequested toestablishamodeltopredict thetime of the bloomphenomenon,in orderto givea generalprediction forthefuturewaterblooms.For havinga higherforecast auracyto waterblooms,by paringsome statistics,we selectsome factorswhich can cause abig influencein waterblooms.We chooseXiangxi Riverwater qualityinspection reportas the data source,process thedata in a normalizingway,and build a work model,we alsousethe Matlab software to screendata repeatedlyby using the methodof crosscheck todetermihestandardization of waterbloomshappening.3.2The solvingsteps fortask oneStep1:Aording tothe analysis,the maininternal factorof influencingwaterbloomsbreeding isnutritive salt,such asN,P isnecessary nutritionelements tothe growthof algae,followed bythe water,the optimum temperature of algae blooms in rapidbreeding is2530C.Moreover,moderate lightconditions are also conducivetotheproduction andagglomeration of algae blooms.Under the5001000lx lightintensity algaegrowth ismore quickly,and PHvalue,surface windspeed andgeography,water temperaturearealsoother factorsto effectthe growthofwaterbloom.We canbuild athree-tier work model,and selecttwo periodwhich notbelong tothe waterblooms time and nottransit into the waterblooms timeyet under the total nitrogen(TN),total phosphorus(TP),water transparency(SD),water temperature(WT),and PHtotal fiveenvironment variabledata as the workinput layer of thesystem.By lookingfor information,found thatwater chlorophylla concentrationis themost directindicators ofstanding cropofalgae in water,sothe total chlorophylla concentrationin waterbody is theoutputof the model.Aording tothe chlorophylla concentrationprediction,we canindirectly forecastthe algaeblooms.The workstructure asshown:InputlayerTransition layerOutput layerIll.1Step2:When webuildaworkmodel,its importantto choosethetransition layerof the numberof nodes.Because thetransitionlayernode numberis different,the workmodel outputis different.The choiceof excessivelayernodenumber directlyaffect theoutputof the work,then affect the performanceofthe work.This Paperdetermines the numberofnodes in thetransitionlayer byusingtheempirical formula.In thisempirical formulaJ=+m nJ standsforthetransitionlayernodenumber,m is the numberof input layer nodes,nisthe numberof outputlayer nodes.Step3:We processdata byusing standardnormalization tounify themand centralizedimensions ofeachfactor to aeleratethe trainingspeed ofwork and the order of magnitude.By usingthe Matlabs prestd,poststd andtrastd functionto extractdata andset thestandard normalizedprocessing,inorderto makeeach groupof databees themean valueis0and thevariance is1.The specificusage ofthese functionsrefer tothe attachment.Step4:Select thefirst kinputsampleand thecorresponding expectedoutput randomly.()12()(),(),()=?nk xk xk xk x()12()(),(),()=?qk d k dk dkod Step5:Calculate eachnode ofthe excessiveinput andoutputlayer.1()()1,2,=?=?nh ihi hihi k wxkbhp()f()1,2,=?h hho k hi k hp1()()1,2,=?=?po ho h ohyik who kb oq()f()1,2,=?o oyo k yikoq Step6:Using workdesired outputand theactualoutput,putethepartialderivativeoferrorfunctionoftheoutputlayernode()ok.?=?oho o hoyi e ew yi w()()()?=?pho h oo hhhohow hok byi kho kww211()()2()()()=?=?qo oooo oood k yo kedk yok yokyi yiStep7:With the connectionweightsfrom transitionlayer tooutputlayer,theoutputlayer()o kandtransitionlayertocalculateerrorfunctionagainst thepartialderivativeoftransitionlayer neurons()h k.()()?=?oo hho ohoyie ek ho kwyiw1()()()()()=?=?=?hih hihnih ihh iiihihhi ke ewhik ww xk bhikx kww21212111()()()2()()()1()f()()2()()1()f()()2()()=?=?=?=?qo oohh hhqo oohh hqpo hohooh hhhd kyo kho k ehik hok hi kd k yikhokhok hikdkwhokbho khokhik11()()()f()()()f()()=?=?=?qho oo hoohqohohhoho kdkyokyik whikk whik k Step8:With theoutputoftheoutputlayerandtransitionlayerneurons()okto fixtheconnectionweights()how k.1()()()()()+?=?=?=+ho ohhoN Nhohoohew kk hokww wkhok Step9:With eachtransitionlayerneurons()h kand theinputs ofeach inputlayerneuronsto correctconnection power.1()()()()()()()+?=?=?=?=+hih hiih hihN Nihih hihikeewkk x kwhikww wkxk Step10:Calculate theglobalerror.2111()()2=?q mook oEdky kmStep11:Select the three gorges reservoir bay,XiangxiRiverand investigateinto itswater sampling,then we cangetthe contains of total nitrogen,total phosphorusand water temperature,PH,water transparency,and dissolved oxygen.Figure2shows5environment variablesof XiangxiRiver Baysuch as total nitrogen,total phosphorusand chlorophylla concentration as thebasis of blooms outbreakwith themonitoring value of samplingtime(MatchOctober,xx).In addition,we alsogive themonitoring valueoftherelevant statistics.The specificusage ofthese functionsrefer tothe attachment.Ill.2Step12:In orderto improve the process of buildingamodelofthe neural worktopredictperformance,weselectenvironment variablehistorical datawhich delaysone weekas workinput atfirst.But consideringthat oscillatoriabegins toappear in the process of monitoringin thefifth weeks,so wefinal choicea totalof18weeks whichstarting from the twiceweeks tomonitor dataas the original data to modelbuilding.Step13:Based on theworkstructure modeland theMatlab softwarein figure1,applying totheMatlabs tansig(),logsig()functions,we screenthe training data set.Comparing the training resultswithactualchlorophyllaconcentration,theresultcanbeshown infigure3:Ill.3The figure3shows that the concentrationof chlorophylla predictedvalue and actual valueare betterfitting degree,error rangebetween0.01to0.001.Aording tofigure3,you cangenerally getthe bloomshappened periodrange in15weeks.3.3Methods usedin thetask oneMethod one:normalization Datastandardization(normalized)processing isa basicwork ofdata mining,different evaluationindex tendsto havedifferent dimensionsand dimensionalunits,it willaffecttheresult ofdata analysis.Iin orderto eliminatethe dimensioninfluence betweenindicators,we needdata processingstandardization tosolve theparability amongthe indexdata.After dealingwith thedata standardization,the originaldatas eachindex canbe inthesameorderofmagnitude,which issuitable for a prehensiveparative evaluation.Normalization methods:Min-Max standardization,also calledthe deviationof standardization,which isthe lineartransformation oftheoriginaldata.It canmake theresult valuemapping between0,1.Conversion functionis asfollows:The Maxisthemaximum ofsample data,and theMin isthe minimumvalueofsample data.Once ithas newdatatojoin in,it canchange thefigure ofMax andMin,thus weneedtodefine again.Using Matlabsoftwaretorealize normalization.Structures refertotheattachment.3.4Method two:Cross-Validaton Overfittingisaproblem oftenencountered intheneural work trainingcircle inordertosolve theneural workfitting andimprove theneural workgeneralization abilityof induction.We usecross testto dealwith the whole data set,and dividethe entiredata setinto threeparts:training data set,validation data set andtest data set.We choose18data setfrom thetotal26as thetraining data set,and select4data setrandomly as the calibrationdataset,also weselect4datasetrandomly as a test dataset.In the processofbuilding model,we ultimatelydetermine thatwe regard8,14,18,23weeks correspondingdataset as avalidation dataset,and10,15,27,30weeks datasetastestdatasets,andtheremaining18weeks correspondingdatasetasthetrainingdataset.4The analysisandsolutionof TaskTwo4.1The analysisof TaskTwo Wechoose Tai Lake areaas ourmainly researchareatopredictwaterblooms.Located acrossJiangsu andZhejiang provinces,Tai Lake isthethird largestfreshwater lakein China,between119008-121055E and300OS-3xxN.It islocated inthe Taihu Plain,the southoftheYangtze Riverdelta.It connectsWuxi,Suzhou,Huzhou,and Yixing,thus thewhole riverbasin area is reached36500kilometers.The maincharacteristic of TaihuPlainis higherinthewest,lower inthe east,and hollowinthemiddle.The elevationofthewest andthe northwestground ismorethan5meters,and4to6meters ineast andsoutheast ground.Moreover,YangCheng rivetingarea,the centralof Taihu,Yangcheng,and DianshanLake,the elevationof it is followedbelow2to3meters soastoform atypical saucerwater depressions.As oneofthemost denselypopulated areas,thetotalpopulation of Tai Lakebasin reaches33.475million people,andthe average populationdensity is917per kilometers.Its worthto mention thattheurbanization levelof thatarea isthe toprank inthewholecountry.Tai Lake,asthemost significantfreshwater resourcesin thatarea,isanimportant watersource supplybase tooffer watertothe surrounding largeand medium-sized cities.It alsointegrates thefunctionofwater supply,flood storage,irrigation,aquaculture,tourism andothers asa whole.As atypical shallowlake,paring with the deeplake,Tai Lakehas thefollowing features: (1)The lakeis wide,not deepand oftensuffering windand waves.Aording tothe observation,under thegeneral weatherconditions,Tai Lakewaves in0.5meters orso.And thewaves canreach1meter whenit suffered5or6levels ofwind.Heavy wavesand windscancausethe lakesediment particlessuspended again.Studies showthatthesuspended particlesinthewater isthe mainfactortoinfluence the light,heat andtheprocessof ecologyinthe lake. (2)Tai Lakehas goodwarm conditionsas wellas adequateillumination,andtheannual averagetemperature inlake districtis15.3-16.Especially inJuly andAugust,the averagetemperature reaches28-29.As usual,Tai Lakes averagewater temperatureis1.3higher thanthe air,which canbe upto29-30.And sucha temperatureistheoptimumtemperaturefor microcystin algae tobreed.Because ofthe fullysunshine,2000-2200hours peryear,Tai Lakehas ahigh primaryproductivity. (3)The siltlaying inthe bottomofTai Lakeisthin,generally in20to30centimeters.Under thiscondition,nutrients areless depositionbelow thelake,plus windsand wavesinfluences,Tai Lakesilt beesa nutritionlibrary. (4)Tai Lakeis notonly shallow,but alsohas aflat bottom,theaverageslope isonly19.7,so generally,thewaterspeed isslow.The speedis mainlyconnected withthe windslevel,which isonly obviouslyseen incertain rivernear throughputstream.The generallake flowvelocity isabout10centimeters persecond.In bays,there areslower speedswith5centimeters persecond.Therefore,the diffusionof nutrientsand planktonicalgaeinwater migrationis stronglyinfluenced bythe windand waves,undertheaction ofwind,algae canoften bemixed upand downor driftedwiththewind topile upduring thesummer.The averagecontains ofnitrogen andphosphorus in Tai Lakehave beenhighly recently,cyanobacteria bloomhas beethe normalscene,the pollutionproblem isdifficult tobe solvedinashort time.Because eventhe exogenousinput hasreduced,inalong period,the long-term aumulationof internalnutrient inthelakesediment isstill enoughto supportthe growthof cyanobacteriabloom,it ishard toputanend tothe ourrenceofalgaebloom.4.2The solvingsteps usedin TaskTwo Step1:Check thecontainsoftotalnitrogen,total phosphorus,water temperature,water transparency,and dissolved oxygen in20weeks agobefore waterblooms ourred,and alsothedataof variousfactors afterit happened.The resultsis shown in appendixfour.Step2:Normalize theputed dataandputthem intothe modelwe madeinTaskOne,we canevaluate thefitting degreeofthepredicted valuesandactualvalues,which isshown infigure4.Ill.4Figure4shows thatthenumberof chlorophyllaconcentrationin TaiLake beforeand after16thweekreaches thehappening dtandard,blooms our,which aordswiththereality.It alsotestify theauracyofthe model.Step3:Make aninterventionplan:Assuming thatother factorsare thesame withthe taihulake,and reducethetotal phosphorus,totalnitrogen,water temperature,PH,dissolvedoxygeninto1/3oftheorigin,and thenplug intothe modelto gettheresultwhich isshowninfigure5-1to5-5.Change temperatureChange PHIll.5-1Ill.5-2Change thedissolvedoxygencontent ChangeTP Ill.5-3Ill.5-4Change TNIll.5-5From figure5-1to5-5,wecanknowthatthe variationcoefficient ismore significantdifference afterchange theTP,and coefficientof variationsuch aswatertemperature,TN thedifference isnot particularlyobvious.This showsthatthetotalphosphoruscontent isthe maininfluence factorsofbloomsourred.Because ofthe rapiddevelopmentofYangtze Riverdelta,a lotof factoriesbuilt aroundthe TaiLake,which causea largeportion ofthe containingorganic saltposition ofsewage intothe TaiLake.And thephosphorus emissionsaounted fora significantproportion.And basedonthatwecanknow alarge partofthereason waterbloomsourin thatareaistoo muchphosphorus emissionswhich emittedfromthenearby factoriesAs aresult,we focuson thecontent ofTP inour interventionplan toreduce theiremissions inthe TaiLake.On theone hand,which canslow downthe frequencyof happeningwaterbloomseffectively,ontheother hand,we onlycontrol theTP thisone factor,which cangreatly reducethe costsin economicaspects.After performingthe interventionplan,the frequencyofthebloomsinTaiLakeregion will be greatlyreduced.In thesurrounding areasofTaiLake,such asGongHu andMeiLiang bayas wellasthesurroundingareasof NaTaiHu,waterbloomsalso canbe reducedgradually.Because ofthe highwater levelin theseareas,itiseasy tolead waterto flowbackward andmakealarge numberof cyanobacteriabloom pouredintotheriver.But theprobability willbe reducedafterperformingtheinterventionprogram,beside,the coastalareaswater qualitywill improvea lot.This interventionplan canimprovethewater qualityinTaiLake andthesurroundingareas,which alsoincrease theresidentshealth index.tthesame time,the developmentof fisheries,such asplanting industry,tourism industrywillbemore prosperousthan ever.5Evaluation andpromotion ofthemodelAdvantages ofthemodelThe establishmentofthethree layerworkmodel,the useof normalizationand crosstesting canmake theprocess moreclearly,which isconvenient tofacilitate andanalysisandmake neural work predictionismoreaurate.The sensitivityanalysisofeachfactorin interventionplan canalsoreducethe costs.Disadvantages ofthemodelWhen weresearch andanalysis theproblem,weregardone weekasatime unitbut ignoringthelighttemperature change,we alsoputthechlorophyllaconcentrationastheonlystandard,which causesome errors.Model generalizationLess economicinput、large feasibilityand suitablefor popularizationand application.6Reference documents1Huangwei.Cyanobacterial bloomssignificantly correlated factors identification、Short-term predictionand regionalcooperation governanceresearchD.Shanghai Univerity,xx2Wanglan,Cai Qinghua,Zhangmin,Tanlu,Xu Yaoyang,Kong Linghui.Xiang Riverbay inthethreegorgesreservoir,the algaebloomsinsummer thespace-time dynamicand itsinfluencingfactorsJ.Chinese Journalof AppliedEcology,xx,08:1940-1946.3Liuxia.Algae bloomsinTaiLake dynamicenvironment,andtherelatedfactorsof researchforalong timeD.Huazhong Universityof Scienceand Technology,xx.4Liu Wenjie.Inland lakecyanobacteria bloomsof remotesensing monitoringand evaluationresearchD.China Universityof Geosciences,xx.5Zhang Yanhui,Li Weifeng,Chen Qiuwen.TaiLakewaterleveland itstimeandspace distributioncharacteristics ofthe ecologicalenvi