چکیده مقاله
Informal settlements in megacities face significant challenges in local governance due to resource scarcity, population density, and inadequate infrastructure This study aimed to analyze and predict the inefficiency of local policies in the development of informal settlements in Mashhad A descriptive analytical research design with a quantitative and predictive approach was employed, and data were collected through field questionnaires and secondary sources The study population included informal settlements in Mashhad, and a multistage cluster sampling method was used to select 384 participants Data were analyzed using a deep neural network model to identify complex relationships between governance indicators, household economic status, and policy inefficiency Results revealed that citizen participation mean 2 4 out of 5 , accountability, and institutional efficiency had the greatest impact on policy inefficiency, with the predictive model achieving an accuracy of 82% and R2 = 0 75 Additionally, the southern and southeastern zones exhibited the highest levels of inefficiency The model's results facilitate targeted interventions and optimal resource allocation, emphasizing that reform policies should be multidimensional and evidence based This study provides a practical tool for informed decision making and enhancing local governance in informal settlements
کلیدواژهها
نویسندگان
Esmaeel Aghaei
Mohsen Kafashian
Mohsen Kafashian
Esmaeel Aghaei
شیوه ارجاع
Aghaei, Esmaeel and Kafashian, Mohsen,1404,Predictive Analysis of Local Governance Policy Inefficiency in the Development of Urban Informal Settlements Using Deep Neural Networks: A Case Study of Mashhad Metropolis,11th National Conference and 4rd International Conference on Urban Planning and Management,Mashhad
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مجموعه مقالات یازدهمین کنفرانس ملی و چهارمین کنفرانس بین المللی برنامه ریزی و مدیریت شهری14 آبان 1404 · مشهد