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Trip Generation ModelIn the 1880s E.G. Ravenstein published his laws ofmigration based upon a study of the 1881 census(Anjomani 2002). His main points were as follows: Mostpeople migrate short distances; fewer people migrategreater distances. Mathematical statement for themigrations could be present as:1N ij =Dwhere N - is the number of migrants from town i to townj;D - is the distance between the two towns.But, it cannot be used as a predictive tool, i.e. it cannot beused to determine the level of migration between twotowns; it does not take into account other factors such asemployment levels.The Ravenstein's formula was upgraded and theregression model adopted for the trip production andattraction models and these are:0.41⎛0.720.13* ⎜Pop_i*Pop_j *KGDS_jD_DN_MIGR=⎝1.730.90d(t-GIS) *KGDP_i *KGDP_jwhere,i – index of municipality of origin;j – index of municipality of destination;D_DN_MIGR - commuter’s workers between Slovenemunicipalities (Census 2002);POP_i – population in zone i;POP_j – population in zone j;d(t-GIS) - time-spending distance calculated inOmniTRANS using the road network 2004 (in minutes);KGDP_i - coefficient of Gross Domestic Product fromstatistical period 2003 in zone i;KGDP_j - coefficient of Gross Domestic Product fromstatistical period 2003 in zone j;KGDS_j - coefficient of Gross Salary = GDP in themunicipality / GDP in Slovenia in zone j;UEMJ_i - coefficient of unemployment in themunicipality = registered unemployment in themunicipality of origin / registered unemployment inSlovenia in zone i;UEMJ_j - coefficient of unemployment in themunicipality = registered unemployment in themunicipality of destination/registered unemployment inSlovenia in zone j.Specification of the model databaseThe basic model for this study consists of five jointlydependent endogenous variables. They include the rate ofij,0.650.23*UEMJ_i*UEMJ_j0.040.15⎞⎟⎠population growth (POP_zone(I, J)), the rate of timespending distances d(t-GIS), rate of Gross DomesticProduct (KGDP_zone(I, J)), the rate of Gross Salary(KGDS_J) and the rate of unemployment growth(UEMJ_zone(I, J)).Index i represent origin and j represents destination of aregion. Figure 1, as a quick reference, highlights all modelvariables for a few relationships (all database of gravitymodel includes 7099 relationships, those are thatrelationships, between which population migrations arehappens), including their expected signs.All described variables are expressed as the logarithm of thevariables in producing the regression model. As such, thecoefficients will constitute the elasticity’s.The simultaneous consideration of migration and economicvariables is reflected in our selection of endogenousvariables. In addition to the two-way causation between thesevariables, the more intricate relationships should also beconsidered. For example, the effect of the destination'smanufacturing employment on migration is thought to be afunction of employment and population variables. Similarly,it is hypothesized that unemployment at the destinationaffects other endogenous variables, which, in turn, affectmigration.Figure 1. Model database representation (fragment).The model of the influence of the newly builthighways in terms of employment and commutingbetween the regions of Slovenia purpose is to show theimprovements of daily commuting and time spendingdistances between regions after the new investments inroads, which will also induce the transit traffic inSlovenia, influence the demand of land and land use in thecentral places of Slovenia. These parameters needed forsuccessful regional development.Annual Proceedings of Vidzeme University College “ICTE in Regional Development”, 200674
These results of a model require a short representationof the Excel model called gravity model which has beendeveloped by the University of Ljubljana and afterrepresented into WEB by this paper author.Model variables explanation:1-ID REG I- code for region of origin;2-IDMUNI- code of municipalities of origin;3-IDREGJ - code for region of destination;4-ID_MUN_J- code of municipalities of destination;5- d(t)2004 - time-spending distance in 2004;6- sprd(t) - decrease of time-spending distance 2004-2013;7- skr_p_cap - decrease of time-spending distance percapita (only for those who travel by car) ;8 - d(t)napoved - new time-spending distance for thosewho travel by car;9 - delezOV - percentage of commuters traveling by carin 2002;Figure 2. Short gravity model data.10 - dm 2002 - commuters in 2002;11 - dmnapoved - new volume trip (number ofcommuters) considering decrease of time-spendingdistance for those who travel by car;12 - % - percentage of difference in volume trip 2002 -2013;13 Stevilo - difference in volume trip 2002 - 2013PROBLEM SOLUTIONThe MySQL storage and PHP scripting languagewere used in producing the web page of the gravitymodel. MySQL and PHP is an open source projects ofthe Apache Software Foundation and, not surprisingly, itis the most popular Apache HTTP server add-onmodule, with around 40% of the Apache HTTP servershaving PHP capabilities (O'Reilly 2002). PHP isparticularly suited to web database applications becauseof its integration tools for the Web and databaseenvironments. In particular, the flexibility of embeddingscripts in HTML pages permit easy integration with theclient tier. Both PHP and MySQL are easy to use, fast,free, and powerful.Web-based model applicationWEB based gravity model initiative is anapplication of GIS software program that provides theuser with the tools needed to map, measure, andanalyze urban migrations. WEB based gravity modelapplication enables users to analyze how Slovenianinfrastructure affects: time-spending distances;value of population migration; changes of populationmigration in way of infrastructures changes. With thehelp of WEB based gravity model, local people can getinvolved with the way their communities grow anddevelop. This computer application helps the user build abetter, more sustainable community for the future. Italso allows people to work together to find constructivesolutions in the decision making of the populationmigration in future.In WEB based gravity model user throughGraphical User Interface (GUI) (see Figure 3) can makehis choose:• The region of origin;• Region of destination.After that, model will show results with detailedmap of Slovenian municipalities. Here user through GUIcan make his choose:• Municipality of origin (which belongs to chosen -region of origin);• Municipality of destination (which belong tochosen region of destination).Annual Proceedings of Vidzeme University College “ICTE in Regional Development”, 200675
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ISBN 9984-633-03-9Annual Proceeding
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“Development of Creative Human -
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TABLE OF CONTENTSINTELLIGENT SYSTEM
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INTELLIGENT SYSTEM FOR LEARNERS’
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LEARNER 1GROUP OF HUMAN AGENTSLEARN
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QuantityQuantityFigure 6. Distribut
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LEARNERStructure of theconcept mapL
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WEB-BASED INTELLIGENT TUTORING SYST
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materials to be presented and which
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INFORMATION TECHNOLOGIES AND E-LEAR
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correspondence with the course aim
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projects and through IT. Hence, it
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APPLICATION OF MODELING METHODS IN
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can support configuration managemen
Page 29 and 30: The EKD is one of the Enterprise mo
Page 31 and 32: CHANGES TO TRAINING AND PERSPECTIVE
Page 33 and 34: or an end, yet none of these attitu
Page 35 and 36: make decisions. It cannot be volunt
Page 37 and 38: logs), data and video conferencing
Page 39 and 40: Ability to follow user’s multi-ta
Page 41 and 42: CONCLUSIONSEDUSA method gives us a
Page 43 and 44: in successful SD. Given this situat
Page 45 and 46: SPATIAL INFORMATIONFor the visualis
Page 47 and 48: MOBILE TECHNOLOGIES USE IN SERVICES
Page 49 and 50: learning environment (Learning Mana
Page 51 and 52: ago only some curricula on Logistic
Page 53 and 54: The Web-based version can be access
Page 55 and 56: Web-portal, which incorporates diff
Page 57 and 58: DO INTELLIGENT OBJECTS AUTOMATICALL
Page 59 and 60: Table 1. Examples for introducing R
Page 61 and 62: workable influencing of the process
Page 63 and 64: are handed over to the objects and
Page 65 and 66: • Basic processes, such as wareho
Page 67 and 68: THE ECR E-COACH: A VIRTUAL COACHING
Page 69 and 70: participating in the workshops and
Page 71 and 72: • Assessment modules enable indiv
Page 73 and 74: with pictures and illustrated graph
Page 75 and 76: ECR Question Banknumber category su
Page 77 and 78: educational programme that follows
Page 79: DEVELOPMENT OF WEB BASED GRAVITY MO
Page 83 and 84: CONCLUSIONSThe main goal of work ha
Page 85 and 86: dimension and included within any o
Page 87 and 88: • Resources sharing by providing
Page 89 and 90: Pursuant to the guidelines of elect
Page 91 and 92: tariffs of regulated services have
Page 93 and 94: INFORMATION TECHNOLOGY FOR MOTIVATI
Page 95 and 96: difficult to predict when and for w
Page 97 and 98: Listeners' workon the WebListenersS
Page 99 and 100: PERSPECTIVES OF WEB PAGE AND E-MAIL
Page 101 and 102: INCREASE IN THE NUMBER OF INTERNETU
Page 103 and 104: tourism accommodations (home pages
Page 105 and 106: interactive relationships with clie
Page 107 and 108: • The data obtained by the resear
Page 109 and 110: Central Statistical Bureau of Latvi
Page 111 and 112: departures for 1995 are taken from
Page 113 and 114: 120100maximumworldminimum806040200-
Page 115 and 116: 140120maximumworldminimum1008060402
Page 117 and 118: would be a promising extension. Cur
Page 119 and 120: AN OVERVIEW OF THE AGENT − BASED
Page 121 and 122: Suitability for social system simul
Page 123 and 124: 6. MASONDescription:MASON is a fast
Page 125 and 126: Suitability for social system simul
Page 127 and 128: could be bad particularly when over
Page 129 and 130: (for 10 repeat &| CCar[]->runfor);P
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• Streaming audio• Collaboratio
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NECESSITY OF NEW LAYERED APPROACH T
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Up to now, there has only been limi
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aaaaa6= −aa2,1 = − a0,3226= −
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∂ u∂x∂ u∂y2 2+ b = 02 2wher
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a6,3= −2030a4,5−130a4,3- - - -
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0,10,20,30,4( )Mag x y y Ge wx2, =
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Example 1. To understand better the
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Therefore, further the following co
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SOLUTION OF THE THREE-DIMENSIONALEQ
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Mag1, m , m , m1 2 3= mm1 m2m32 2 2
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MagMag0, m , m , m1 2 31, m , m , m
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CONCLUSIONSThe basic content of thi
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