Potential classification of Smart Village – Smart Economy with Deep Learning methods

2021 ◽  
Vol 2 (3) ◽  
pp. 147-162
Author(s):  
Runanto Runanto ◽  
Muhammad Fahmi Mislahudin ◽  
Fauzan Azmi Alfiansyah ◽  
Maudy Khairunnisa Maisun Taqiyyah ◽  
Eneng Tita Tosida
Keyword(s):  
Data Mining ◽  
Deep Learning ◽  
Development Program ◽  
City Development ◽  
Target Class ◽  
Learning Methods ◽  
Development Goals ◽  
The Village ◽  
The City

Development gap in the city and village is still happening on Indonesia. It happened because of the massive urbanization factors. Poverty in the Indonesian villages are relatively higher than on the urbans. In order to reach the maximal city development, Ministry of Village, Development of Disadvantaged Regions and Transmigration of Indonesia created a sustainable village development program namely Village’s Sustainable Development Goals (SDGs) and optimized the village potential data. This study aimed to design the smart village – smart economy classification system by using deep learning methods on village potential data on Indonesia at 2020. The method used in this study is data mining processes namely KDD (Knowledge Discovery and Data mining). The result in this study showed the best models were obtained which consisting of 2 hidden layers and each layer is 128, 128 layers which using target class from the process of calculating the score is able to reach 94.93% of the accuracy from the training process and 96% on the testing process and succeeded to classify the potentials of smart village – smart economy.

Classification of audio codecs with variable bit-rates using deep-learning methods

2020 ◽  
pp. 102952
Author(s):  
Atieh Khodadadi ◽  
Soheila Molaei ◽  
Mehdi Teimouri ◽  
Hadi Zare
Keyword(s):  
Deep Learning ◽  
Learning Methods

Producing Urban Space

2021 ◽  
pp. 83-112
Author(s):  
Dolly Kikon ◽  
Duncan McDuie-Ra
Keyword(s):  
Urban Space ◽  
Urban Politics ◽  
Contentious Politics ◽  
Customary Law ◽  
Municipal Elections ◽  
Constitutional Protection ◽  
Village Level ◽  
The Village ◽  
The City

This chapter analyses the efforts to make Dimapur more city-like. Beginning with attempts to hold municipal elections with reserved seats for women in 2017, we navigate the deeply contentious politics around the classification and re-classification of space in the city. As the largest city in a tribal state, Dimapur is an experiment in the production of legible urban space in areas with customary law and constitutional protection. At present the experiment is provoking deep anxieties. Producing legible urban space from the collection of settlements, villages, barracks, commercial zones, ceasefire camps, encroached tracts, and wastelands under various socio-legal regimes is rarely coherent and often chaotic. We argue that the city is a space to challenge and transgress customary law in ways unthinkable at the village level. However, transgression was a catalyst for crisis, a scenario likely to remain constant in urban politics for the conceivable future.

scholarly journals Utility of Deep Learning Methods for Referability Classification of Age-Related Macular Degeneration

2018 ◽  
Vol 136 (11) ◽  
pp. 1305 ◽  
Author(s):  
Phillippe Burlina ◽  
Neil Joshi ◽  
Katia D. Pacheco ◽  
David E. Freund ◽  
Jun Kong ◽  
...  
Keyword(s):  
Deep Learning ◽  
Macular Degeneration ◽  
Age Related Macular Degeneration ◽  
Learning Methods ◽  
Age Related

scholarly journals Reengineering of processes of classification in neural intellectual information systems of city development

2018 ◽  
Vol 170 ◽  
pp. 01128
Author(s):  
Vadim Belousov ◽  
Pavel Kurochka ◽  
Tatyana Nasonova ◽  
Tamara Narezhnaya ◽  
Dmitriy Spitsov
Keyword(s):  
Information Systems ◽  
Final Decision ◽  
City Development ◽  
Criterion Function ◽  
Number Of Clusters ◽  
Universal Algorithm ◽  
City District ◽  
The City ◽  
Municipal Economy

In this article reengineering of processes of classification of objects in neural intellectual information systems of city development in the conditions of multi criteria approach is considered. The universal algorithm of calculation of cumulative total opinion of experts of the city district on the basis of a median of Kemeni who allows to order in the most reliable and objective way clusters rankings in the complex multilevel structures representing objects of municipal economy is offered. For receiving reliable results of an indistinct clustering it is necessary to reproduce the specified algorithm repeatedly at a certain number of clusters for various initial indistinct splitting and to compare values of criterion function of indistinct splitting which were received, for the purpose of adoption of the final decision on a necessary indistinct clustering.

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