An Intelligent Method for Industrial Location Selection: Application to Markazi Province, Iran

Decision-making and selection are important and sensitive aspects of planning. An important part of land-use planning is the location of human activities. Locating activities in the right places determines the future space of a region. Selection and definition of natural and human indices and criteria for location always face uncertainty. Thus, this study aimed to develop an intelligent method for industrial location. In this study a developmental-applied approach was used along with a descriptive-analytical method for data analysis. Through the review of related literature and a Delphi survey, 18 criteria were extracted and 6 main components were categorized. The data were analyzed and modeled by GIS, MATLAB software, and the Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) methods. For each modeling three industrial domains were extracted, i.e. weak, medium, and premium. A total of 42,968 hectares of premium industrial location with a score higher than 0.7 resulted from combining the produced maps. Other important findings were related to the architecture and methodology applied in the research based on computational intelligence and knowledge-based systems to analyze and understand the processes that influence the score of locations. The novelty of this method lies in the use of high computing power and information evaluation based on artificial intelligence (AI), making it possible to analyze and understand the processes influencing industrial location. Abstrak. Pengambilan keputusan dan seleksi adalah aspek-aspek penting dan sensitive dalam perencanaan. Bagian yang penting dalam sebuah perencaan penggunaan lahan adalah terkait lokasi kegiatan manusia. Alokasi kegiatan manusia pada tempat yang benar adalah penentu ruang masa depan dari suatu wilayah. Dalam hal seleksi dan definisi index, juga kriteria lokasi selalu menghadapi ketidakpastian. Sehingga, studi ini dilakukan untuk mengembangkan metode yang berguna dalam alokasi industri. Pada artikel ini, digunakan pendekatan terapan-terkembangkan dengan metode analisis deskriptif dalam hal analisis data. Berdasarkan tinjauan pada literatur terkait dan survey Delphi, 18 kritersia diekstraksi yang dikategorikan pada 6 komponen utama. Data dianalisis dan dimodelkan menggunakan GIS, MATLAB, Fuzzy Inference System (FIS), dan metode Adaptive Neuro-Fuzzy Inference System (ANFIS). Untuk setiap model, tiga domain industry ditentukan, yakni: lemah, moderat, dan premium. Terdapat lokasi industry premium dengan total 42,968 ha dengan nilai lebih dari 0.7. Hasil penting lainnya berkaitan dengan arsitektur dan metode terapan dalam penelitian yang berdasar kepada ilmu komputasi untuk memahami proses yang memengaruhi nilai untuk suatu lokasi. Kebaruan dari metode ini ada pada penggunaan model komputasi tinggi dan evaluasi informasi berdasarkan kecerdasan buatan (AI) yang memungkinkan untuk melakukan analisis dan memahami proses yang memengaruhi lokasi industri. Kata kunci. Fuzzy Inference System (FIS), Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), lokasi industri, Provinsi Markazi.

Niederösterreich als Zentrum und Peripherie

Lower Austria as Centre and Periphery. As the embodiment of dynastic Austria, Lower Austria represents a core region in political, economic and cultural terms. Its role in the interregional division of labour was that of a highly developed industrial location. The interplay between politics and economics saw the formation of a regional stage of global capitalism, contributing to the international competitiveness of Habsburg Cisleithania in European comparison. While ethnic and religious difference played a very minor role, the regional diversity was dependent on strong disparities that gave rise to pronounced anti-centralist regional identities, especially in peripheralized areas of the land.

O Método de Ponderação de Fatores como Critério de Localização Industrial / The Factor Weighting Method as an Industrial Location Criterion

O presente artigo tem como objetivo avaliar critérios de escolhas voltadas à localização de indústrias, em especial utilizando o método de ponderação de fatores. Para sua elaboração foi utilizado uma abordagem exploratória e qualitativa, tendo como critério aprofundar o conhecimento da teoria de localização e avaliar características do método de ponderação de fatores. Como resultado, foi possível observar que ponderar os vários fatores que são essenciais na escolha da localização contribui para a redução de riscos e incertezas no momento da instalação de uma indústria. O artigo contribuiu ainda para ressaltar que o método de ponderação de fatores utiliza todos os fatores relevantes no estudo da localização, contribuindo para um resultado mais objetivo, podendo ser considerado o mais adequado e o mais abrangente na geografia locacional.