Network costing analysis

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Network costing analysis

  1. 1. NETWORK COSTING ANALYSIS (SAMPLE ASSIGNMENT) Our online Tutors are available 24*7 to provide Help with Help with Network Costing Analysis Homework/Assignment or a long term Graduate/Undergraduate Help with Network Costing Analysis Project. Our Tutors being experienced and proficient in Help with Network Costing Analysis ensure to provide high quality Help with Network Costing Analysis Homework Help. Upload your Help with Network Costing Analysis Assignment at ‘Submit Your Assignment’ button or email it to . You can use our ‘Live Chat’ option to schedule an Online Tutoring session with our Help with Network Costing Analysis Tutors. A neural network based dynamic forecasting model for Trend Impact Analysis Main Function.m AdvancedTIA() % rand('state',0); -- In case you want to fix the seed; for testing purposes NumS=100,000; NumE=3; NumY=2; TMaxMx=xlsread('Time_Max_Impact.xls'); MaxImpMx=xlsread('Max_Impact.xls'); TSSMx=xlsread('Time_SteadyState_Impact.xls'); SSImpMx=xlsread('Steady_State_Impact.xls'); ProbOccMx=[]; ProbOccMx(:,:,1)=xlsread('High_Sev.xls'); ProbOccMx(:,:,2)=xlsread('Medium_Sev.xls'); ProbOccMx(:,:,3)=xlsread('Low_Sev.xls'); TMax=[]; MaxImp=[]; TSS=[]; SSIMP=[]; SrMx=[]; SrMx=ones(NumY*12, NumS); for s=1:NumS for e=1:NumE info@assignmentpedia.com
  2. 2. for y=1:NumY d=GenerateDegreeSeverity(e,y,ProbOccMx); if d>0 TMax=TMaxMx(e,d); MaxImp=MaxImpMx(e,d); TSS=TSSMx(e,d); SSImp=SSImpMx(e,d); m=randint(1,1,[1,12]); FracChgVect=ComputeFracChgVect(m,y,NumY,MaxImp,SSImp,TMax,TSS); SrMx(:,s)=SrMx(:,s).*FracChgVect'; end end end end load TData % The data we used in the illustrated example (paper) [net,eTrn,eTst] = NN(timeSeries,numInput,numOutput,hL,lFs,lR,errorGoal,epochs,momentum); SrMx=GenSrMx(SrMx,net,NumS,NumY); DrawTIA(NumY,SrMx,timeSeries); SSUpdate.m function[out]=SSUpdate(Idx,MaxImp,TMax,SSImp,TSS,NumY) FracChgVectSS=[]; NumM=NumY*12; if MaxImp==SSImp FracChgVectSS(1:min(NumM,Idx+TSS)-(Idx+TMax)+1)=SSImp; else
  3. 3. for i=1:min(NumM,Idx+TSS)-(Idx+TMax)+1 FracChgVectSS(i)=MaxImp-SSImp/TSS*i; end end out=FracChgVectSS; MaxUpdate.m function[out]=MaxUpdate(Idx,MaxImp,TMax,NumY) FracChgVectMax=[]; NumM=NumY*12; if TMax==0 FracChgVectMax=MaxImp; else for i=1:min(NumM,Idx+TMax)-Idx+1 FracChgVectMax(i)=MaxImp/TMax*i; end end out=FracChgVectMax; GenerateDegreeSeverity.m function[out]=GenerateDegreeSeverity(e,y,ProbOccMx) u=rand(1); visit us at www.assignmentpedia.com or email us at info@assignmentpedia.com or call us at +1 520 8371215
  4. 4. d=0; if u<=ProbOccMx(e,y,1) d=1; end if u<=(ProbOccMx(e,y,2)+ProbOccMx(e,y,1)) & u>ProbOccMx(e,y,1) d=2; end if u<=(ProbOccMx(e,y,3)+ProbOccMx(e,y,2)+ProbOccMx(e,y,1)) & u>(ProbOccMx(e,y,2)+ProbOccMx(e,y,1)) d=3; end out=d; ComputeFracChgVect.m function[out]=ComputeFracChgVect(m,y,NumY,MaxImp,SSImp,TMax,TSS) FracChgVect=[]; NumM=NumY*12; Idx=(y-1)*12+m; FracChgVect(1:Idx)=0; FracChgVect(Idx:min(NumM,Idx+TMax))=MaxUpdate(Idx,MaxImp,TMax,NumY); if NumM>Idx+TMax FracChgVect(Idx+TMax:min(NumM,Idx+TSS))=SSUpdate(Idx,MaxImp,TMax,SSImp,T SS,NumY); end visit us at www.assignmentpedia.com or email us at info@assignmentpedia.com or call us at +1 520 8371215
  5. 5. if NumM>Idx+TSS FracChgVect(Idx+TSS:NumM)=SSImp; end out=FracChgVect; DrawTIA.m function[out]=DrawTIA(NumY,SrMx,BaseFr) history=xlsread('Historical_Values.xls')'; med=[]; p5=[]; p95=[]; for i=1:(NumY*12) med(i)=median(SrMx(i,:)); p95(i)=prctile(SrMx(i,:),95); p5(i)=prctile(SrMx(i,:),5); end generalmat=[]; generalmat(1,:)=[history BaseFr']; generalmat(2,:)=[history med]; generalmat(3,:)=[history p5]; generalmat(4,:)=[history p95]; plot(generalmat') visit us at www.assignmentpedia.com or email us at info@assignmentpedia.com or call us at +1 520 8371215

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