Housing Growth Potential Based Fuzzy Simulation Zonal Ranking: A Case Study Of Indian Metropolitan
Notice bibliographique
Résumé
Population explosion, industrial development and urbanization are closely interknitted and as such forms a global phenomenon.India, being a third world country has been undergoing through this process in a significant way. The Class-I cities and the Metropolitan cities in particular are under rapid urbanization process. Therefore, these centers are experiencing tremendous pressure on resources and urban infrastructure. In Indian Urban system, the interplay of heterogeneous socio-economic groups, infrastructure system components and resources constraints are subjected to urbanization ambivalence. In this process, urban housing sector has been worst affected with clear cleavage between supply and demand, resulting in huge housing shortage. Therefore, the urgency to reduce the gap between housing requirement and supply can not be underscored. The Indian metropolitan under study is an evolved city. It has recorded highest growth rate in the region as well as state. It has experienced one of the fastest growth rates even at the national level. With the rapid growth the city boundaries are increased. For the sake of administration the area under study is divided in seven zones, but for the purpose of technical study the metropolitan area is divided into twenty various study zones. The delineation was based on population distribution and aerial features. Zonal housing growth potential can be defined as ability of a zone to attract the house demanding population to satisfy their actual demand in the varying affordable manner. The housing Growth Potential varies from zone to zone. It is a complex phenomenon and depends upon various varying parameters. On the basis of various pilot housing studies and correlation findings few major factors were found highly influencing.Therefore, the parameters involved are pertaining to land, where the land value plays the major role. Secondly road features like accessibility and road area network are significant. Thirdly the utility services provided to the people are also important. Apart from this, the ongoing Housing activities and the population density are also playing the major role. The Urban area is dynamic in nature. The urban zones have built in potential to attract the people and thus influence the entire city also. Very surprisingly it can be stated that the zonal potential for housing growth varies with time and policies of the planners. It is a unique exhibition of manmade and natural interplay. 1 Asst. Professor, Civil Engineering Dept., S.V. National Institute of Tech., Surat, India Phones +91 261 222337174, + 91 9427148108, macwan112@yahoo.co.in 2 Professor Emeritus, Civil Engineering Dept., S.V. National Institute of Tech., Surat, India. Phone + 91261 2211967 June 14-16, 2006 Montreal, Canada Joint International Conference on Computing and Decision Making in Civil and Building Engineering
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».