Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, University of Palermo, Workshop 2009) 18-20 June 2009, University of Palermo, ItalyItaly Intelligent analysis for Intelligent analysis for
historical macroseismic historical macroseismic damage scenariosdamage scenarios
Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Cinzia Zotta,
Laboratory of Urban and Territorial Systems, University of Basilicata, Italy
Lucia Tilio, Maria Danese, Beniamino Murgante
Archaeological and monumental heritage institute, National Research Council, Italy
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
IntroductionIntroduction
Analysis concerning earthquake events, are normally strictly related to damage survey.
It is evident that documentary sources concerning urban historical damage can provide useful information for seismic microzonation.
This research concerns historical earthquake (1930) damage related to towns of a seismic area of southern Italy (Vulture district, Basilicata).
4,000 dossiers compiled by the Special Office of Civil Engineers have been analyzed.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
IntroductionIntroduction
Why Rough Set Analysis for the analysis of earthquake events?
o The aim is to verify the dependence of the damage level attribution to each building from some socio-economical local dynamics
o All available variables have been take into account and searching some patterns, able to create a cross-data control.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Information System Information System A) (U, IS
Rough setRough set
attribute) of (domain set value V Aa a
Let U be a nonempty finite set of objects called the universe
Let A be a nonempty finite set of attributes
nxxxxxxx ,...,......... , , , ,,U 654321
3 2 1 ,, A AAA
4 ,3,2, 1V
2, 1V
3,2, 1V
3
2
1
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Information System Information System
Rough setRough set
U a1 a2 a3
x1 2 1 3
X2 3 2 1
X3 2 1 3
X4 2 2 3
X5 1 1 4
X6 1 1 2
X7 3 2 1
X8 1 1 4
X9 2 1 3
x10 3 2 1
function ninformatio V U:f aa
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Rough setRough set
U a1 a2 a3 d1
x1 2 1 3 1
X2 3 2 1 4
X3 2 1 3 5
X4 2 2 3 2
X5 1 1 4 2
X6 1 1 2 4
X7 3 2 1 1
X8 1 1 4 2
X9 2 1 3 3
x10 3 2 1 2
Decision SystemDecision System
A decision system is an information system in which the values of a special decision attribute classify the cases
Attributes lConditiona
d-A attributes other a
Ad )A (U, DS d
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Indiscernibility RelationIndiscernibility Relation (B) Ind AB
Bb )b()b( (B) Ind are e jiji xxxx
Rough set Rough set
o The equivalence class of Ind (B) The equivalence class of Ind (B) is called ELEMENTARY SETis called ELEMENTARY SET in Bin B
o For any element xi of U, the EQUIVALENCE CLASSEQUIVALENCE CLASS of R containing xi in relation Ind (B) will be denoted by [Xi] ind B
U/A a1 a2 a3
(X1 , X3 , X9 ) 2 1 3
(X2 , X7 , X10 ) 3 2 1
(X4) 2 2 3
(X5 , X8 ) 1 1 4
(X6) 1 1 2
(X7) 3 2 1
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
)( XxUxLX Bindii
LXUXBX
)( XxUxUX Bindii
Rough setRough set
Equivalence classes
Lower Approximation
Upper Approximation
Boundary Region
)(/)()( UXcardLXcardXB If BX = then the set X is
Crisp If BX ≠ then the set X is
Rough
Accuracy
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Rough set Rough set
Rough membershipRough membership
In order to have an idea about how much an object x belongs to X we define rough membership.
)(
)()()(
)( and [0,1] : )(Bindi
BindiBindX
BindX
x
XxxUx
The rough membership function quantifies the degree of relative overlap between the set X and the equivalence class to which x belongs.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Rough set Rough set
ReductsReducts
A reduct eliminate redundant attributesA reduct is a minimal set of attributes (from the
whole attributes set) that preserves the partitioning of the of U and therefore the original classes.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Rough set Rough set
ReductsReducts
Color Size Shape Accept
x1 G Small Square Yes
x2 B Medium Triangular No
x3 R Small Rectangular
No
x4 G Medium Rectangular
Yes
x5 G Small Square Yes
x6 Y Large Round No
x7 Y Medium Triangular Yes
x8 B Medium Triangular No
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Rough setRough set U = {x1, x2, x3, x4, x5, x6, x7, x8}
A = {color, size, shape} color(green, blue, red, yellow) size(small, large, medium)
shape(square, round, triangular, rectangular)
U/color = {(x1, x4, x5), (x2, x8), (x3), (x6, x7)}
U/size = {(x1, x3, x5), (x6), (x2, x4, x7 , x8)}
U/shape = {(x1, x5), (x6), (x2, x7 , x8), (x3 , x4 )}
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Rough setRough set
U/IND(A) = {(x1, x5), (x2, x8), (x3), (x4), (x6), (x7)}
U/ IND(A –{color}) = {(x1, x5), (x2, x7 , x8), (x3), (x4) (x6)} U/IND(A)
U/ IND(A –{size}) = {(x1, x5), (x2, x8), (x3), (x4), (x6), (x7)}= U/IND(A)
U/ IND(A –{shape}) = {(x1, x5), (x2, x8), (x3), (x4), (x6), (x7)}= U/IND(A)
RED(A) = {(color, size), (color, shape)}
CORE(A) = {color}
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Rapolla
Earthquake 1930
Buildings damage survey 738
Attributes 37
Which relationship between damage and reconstruction
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Busta Fasc Ditta
Owner
Partita
Synthetic cadastral data
Mappale
IndirizzoAddress
Confini dell'immobileNeighbours
ImpresaContractor
Mappale
Parcel
sub
sub
Sott
U
PT
G
IP
IF
IIP
IIFYES NO
Plans
U GF 1F 2F
Floors
YES NO
SectionsDETAILED CADASTRAL DATA
YES NO
Expiry
YES NO
Works carried out bynational government
Revocation of housing subsidies
MAIN TECHNICAL REPORT
pp DATA
Date
Inizio lavori
Fine lavori
PP imp Proposto: PP DMLP data
PP DMLP N
Date
N.
Cost Decree
Supplementary technical report
PS data
PS importo
Date
Cost:
Supplementary subsidy
PSS data
PSS importo
Date:
Cost :
TEST (acceptance of work) CC data
CC imp1
Work time
From
To
Work costs
Ministry comunication
Total cost
Date
CM approvato
CM data1
CM sussidio
CM data2
Subsidy
Date
Prize for quick execution works
Date
USGCM date
Year income
Concession date
Data richiesta ditta
Data proposta Genio
Reddito annuo
Data concessione Ministero
DAMAGE
Direct
YES NO
NOTESNote
PP NN
PA percent%
Valore immobileProperty value
Imponibile fabbr
Cadastral rent
Imponibile totale fabbr
Particelle confinantiNeighbouring parcels urban rural
Sospensione dal
Sospensione al
From
To
Stoppage
YES NOPublic buildingb
GENERAL DATA AND TECHNICAL REPORT
N. fascicle N. tech. report
Form used in order to record and to analyse the documentary data
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Studya lot of information about
reconstruction
budget amount, effective expense, presence of some
interventions, building value, annual income
and so on…
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Building IDReference – Map Reference – Envelope Reference – Folder Reference – Street Building demolitionPublic BuildingReligious Building Withdrawn subventionAssessment of damage DateCosts of works Effectively Funded
Start Work DateEnd Work DateReal estate values of Building Owner Annual IncomeAdoption of tie-beamRoof rebuilding Cracks rebuilding Test date Estimated costs of works Costs of works accounted
Data concerning information about the damage, the post-seismic repairing procedures with buildings techniques description of the housing units and technical-economic-administrative data.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Walls demolition Floors demolitionVault demolitionNew wallNew Floors Toothing projectsShearing stress of masonry (technical procedure for walls rebuilding) Cuci-Scuci (technical procedure for walls rebuilding) Damage description Declared Destroyed (if the building was damaged and declared not reconstructable)Damage class EMSPresence of caves under the building
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
}CONDITIONAL PART
ASSIGNMENT}
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
There is a certain number of rules (25/88) that present a clear discrepancy into damage level attribution:
The analysis permits the identification of such discrepancy and a possible interpretation: differences in damage distribution are not spatially clusterized, but they concerns areas having different social and building features (rich and poor owners, big and small housing, building well preserved and lacking of maintenance ect.)
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
Changes in damage classification seem not to be due to voluntary human influences (e.g. acquaintance with technicians to get increase of damage attribution by favoritism) rather differences may be imputable to other factors, among which:
o Rough initial inspection of buildings (e.g. only some rooms were surveyed, damage assessment was carried out from outside of buildings).
o Different vocational training of engineers entrusted to survey affected housing units.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Case StudyCase Study
o Feature of damage description: during initial post-seismic phases, report of damage included improvements and/or extension works unrelated to the seismic event.
o Incompleteness of descriptive data: administrative/technical parametric information on which the rules are based on, sometimes supply more constraints of some very concise description of effects given by the engineer surveys.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Future developmentsFuture developments
New study area
It is known that during an earthquake the damage to buildings with comparable features can differ enormously between points.In a wider area it could be interesting to analyze also effects of geological surface.
Intelligent Analysis of Environmental Data (S4 ENVISA Intelligent Analysis of Environmental Data (S4 ENVISA Workshop 2009) 18-20 June 2009, Palermo, ItalyWorkshop 2009) 18-20 June 2009, Palermo, Italy
Intelligent analysis for historical macroseismic damage Intelligent analysis for historical macroseismic damage scenarios scenarios Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Fabrizio Gizzi, Nicola Masini Maria Rosaria Potenza, Maria Danese, Cinzia Zotta, Maria Danese, Cinzia Zotta, Lucia Tilio, Beniamino Murgante Lucia Tilio, Beniamino Murgante
Future developmentsFuture developments
Compare Rough Set results with other intelligent methods using Visual Analytics:
o Multiform Bivariate Matrix
o Self-Organising Map (SOM)
o Parallel Coordinates Plot (PCP)