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Enregistrement W6945072554 · doi:10.22111/gdij.2012.426

Analysis of Deathly Road Accidents in Novrooz Holidays of Year 2007 with Climatic Approach Dr. Manochehr. Farajzadeh AslAssociate Professor of GeographyUniversity of Tarbiat ModresAli. BahooshiM. S of Geography

2012· article· en· W6945072554 sur OpenAlexaboutno aff

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Langueen
DomaineEngineering
ThématiqueTraffic and Road Safety
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAccident (philosophy)Road accidentRoad trafficAir temperatureRelation (database)Geographic information system

Résumé

récupéré en direct d'OpenAlex

Introduction Road accident is one of the most important causes of mortality in the world and in Iran. About 24000 people lose their life in road accidents. Several environmental factors have great influences on road accidents that the share of climatic factors such as sliding areas, snow, fog and freezing is more. Different researchers have studied the relation between climatic conditions and road accidents and found significant relations between road accidents and climatic parameters. Noroooz holiday in Iran starts from 21 march and continues for about two weeks. In this period, travel of people increases and consequently increases the road accidents. This study tries to analyze and study the effect of climatic factors on 1756 deathly accidents occurred during the 20-days of Norooz holiday in 2008 in the roads with heavy traffic. Research Methodology Two different data sets were used in this study including the accident data obtained from Police database for the under study period, the statistics showed that during this time, 1756 deathly accident occurred in the main roads of Iran. The collected data covers province name, police station name, day and hour of accident occurrence and the likes. The second data set; include the data of 140 meteorology stations for all climatic parameters such as precipitation, temperature, humidity and so on. Then the distance of accident points based on km were specified on the axes. Also meteorology data for all the stations after being controlled and prepared were entered in to GIS soft ware. Discussion and Results The analysis of climatic conditions in this period reveals that in the 25th, 26th and 29th of Iranian month of Esfand (15, 16 and 19 March) and also 8th, 10th and 14th of Iranian month of Farvardin (28 and 30 March and 3 April) adverse climatic conditions were dominated in most parts of Iran. The analysis of the occurred accidents showed that most of them happened in the first 20Km from the origin between 15 o’clock up to 18 o’clock of local time. In the next step, with respect to the frequency of accident in different days, it was cleared that the number of accidents in the days of 29th Iranian month of Esfand (20 March) and 8th, 9th, 13th and 14th of Iranian month of Farvardin (28 and 29 March 3 and 6 April) has significantly increased. Therefore, it can be concluded that this increase, except for the days that the number of journeys were increased, was mainly due to the bad climatic conditions in the country. Conclusion The result of this study indicates that there is a significant relation between climatic conditions and road accidents in Iran especially during travelling by privet cars. The ability of GIS for analyzing the spatial aspects of accidents with combining descriptive data helps to the evaluation of any point of the country for risk analysis evaluation. The method used in this study can be used in other similar studies and it is clear that the accurate analysis of road accidents in Iran requires a powerful online database in order to decrease mortality rate caused by road accidents. Keywords: Road Accident, Climate, Norooz holidays, Road, Iran. Refrences 1- Abytoraby Masod, Rezaey Moghadam Farazad (2010), the Modeking if accident intensity in urban highways, Transportation reseach Journal. No. 1. 2- Arnof,Estan(2005).Geograpgic Information System,translated by Iranian Survay organization,320P. 3- Andresscu Mircea-Paul, Frost David B. (1998). Weather and traffic accidents in Montreal, Canada. Climate Research, Vol. 9. 4- Andri, J and Oley, R.S (2001). The relation between weather and road safety: past and future, Climatological Bulletin, 24 (3). 5- Ayaty Esmaeyl (1992), Iranian road acidents, Mashhad Ferdosi University publisher, 220 P. 6- Azizi Ghasem, Habibi Nokhandan Majid (2005), the study of spatial and temporal distrbution of frost and slides in Haraz and Dirozkoh roads using GIS, Geographycal reseach, No. 51. 7- Bros(1990).The Safety index method of evolution and rating safe benefits,Highway­Research,Ni.332. 8- Carson and Mongering F (1999). The effects of ice warning sing on ice accident frequency and severity, accident analysis and preventation, No. 33. 9- Edvards Julia B. (1998). The relation between road accident severity and recorded weather, Journal of safety research, Vol. 29, No. 4. 10- Eisenberg Daniel. (2006). The mixed effects of precipitation on traffic crashes, Accident Analysis and Preventation, No. 36. 11- Farajzadeh Manuchehr, Baghada Osman(2005), the evolution of road safety with environmental hazards approach using GIS; study area: Sanandaj- Marivan road, Human scence Jounal, No. 38. 12- Farajzadeh Manuchehr, Gholizadeh Mohamadhosin, Adabi Firozjaei (2010), The analysis of road accident with climatic approach: Karaj- Chalus road, Physical geography research journal,No. 37. 13- Habibi Nokhandan Majid (2005), The study of spatial and teporal distribution of fog and effects on road accident, Geographical research Journal, No, 76. 14- Information Technology office, Road preventation and transportation organization (2006), Satatictics Bulitan. 15- Analysis of Deathly Road Accidents in Novrooz Holidays of Year … Kamali Gholamali, Habibi Nokhandan Majid (1988), Climat and road safty, Road and travelling ministry publisher, 195P. 16- Karami Shahram, Farajzade Manuchehr (2005), The analysis of road accident with climatic approch using GIS; study srea: Firozkouh-Sari road, Human scence Jounal, No. 32. 17- Kamali Gholamali, Habibi Nokhandan Majid (2005). the studty of spatial and temporal distrbution of frost in Iran and its efect on road transportation, Transportation Journal, No. 2. 18- Keay Kevin, Simoonds Lan. (2006) Road accident and rainfall in a large Australian city, Accident Analysis and Preventation, No. 36. 19- Karl, Kim and Leving; (1996). “Using GIS for Improve highway safety”; Computer Environ and Urban System, Vol.20. 20- 20.Mohamadi Hosin, Mahmodi Pyman (2005), the effects of climatic fenomenons on travelling anf accidents in Sanadaj- Hamedan road, Geograph and Rejional development Journal, No. 6. 21- Norrman Jonas, Eriksson Marie, Lindqvist Sven (2000). Relationships between road slipperiness, traffic accident risk and winter road maintenance activity, Climate Research, Vol. 15. 22- Pyden Marjin, Scorfild Richard, Eslyte Dyvid, Mohan Denish, Hydar Adnan, Jarvan Eva, Maters Colin (2006), world report of preventaion of road traphic accident, translated by Jamshid kermanchy, Mehran Sotodeh, Mohamad Hadi Naseh, Tandis Publisher, 230 P. 23- Yamamoto A (2002). “Climatology of the traffic accidents in Japan on the expressway with dense fog;: 11th international road weather conference, Sappro, Japan case study

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,055
Score d'incertitude au seuil0,110

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,095
Tête enseignante GPT0,432
Écart entre enseignants0,337 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

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Citations0
Publié2012
Routes d'admission1
Résumé présentoui

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