scholarly journals Transformer Fault Early Warning System Model Using GSM Network

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
M. A. M. Azmi ◽  
Z. Nawawi ◽  
M. I. Jambak ◽  
M. A. B Sidik ◽  
Y. Z. Arief ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
System Model ◽  
Gsm Network ◽  
Transformer Fault

scholarly journals Transformer Fault Early Warning System Model Using GSM Network

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
M. A. M. Azmi ◽  
Z. Nawawi ◽  
M. I. Jambak ◽  
M. A. B Sidik ◽  
Y. Z. Arief ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
System Model ◽  
Gsm Network ◽  
Transformer Fault

scholarly journals Early warning system model as a resilience of disaster-prone communities

2019 ◽  
Vol 1375 ◽  
pp. 012093
Author(s):  
M Rochim ◽  
A Bajari ◽  
N A Damayanti ◽  
I Bakti
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
System Model

Design of Early-Warning System Model for Gas Explosion

2011 ◽  
Vol 121-126 ◽  
pp. 2643-2647
Author(s):  
Dong Mei Huang ◽  
Xi Kun Chang ◽  
Ye Jiao Liu ◽  
Yan Min Wang
Keyword(s):  
Decision Theory ◽  
Early Warning ◽  
Early Warning System ◽  
Scientific Theory ◽  
Warning System ◽  
System Model ◽  
Accident Risk ◽  
Gas Explosion

Based on the prevention of gas explosion in colliery, and the risk early-warning theory, the characteristic and reason of gas explosion is analyzed. The accident model is proposed according to gas risk mechanism; then based on the accident risk early warning principle and the organization, combines the minds of safety scientific theory and decision theory, the accident model of early-warning for gas explosion is established. Finally, it analyzes and introduces each element, and indicates the implementation, which provide theory basis for safe early-warning on production.

scholarly journals KNN algorithm of early warning system for applied research course

2020 ◽  
Vol 218 ◽  
pp. 01030
Author(s):  
Zian Li ◽  
Cui Zhao
Keyword(s):  
Experimental Data ◽  
Basic Principle ◽  
Early Warning ◽  
Early Warning System ◽  
Applied Research ◽  
Warning System ◽  
System Model ◽  
Manhattan Distance ◽  
Paper Briefly ◽  
Basic Experimental Data

This paper designed a small course early warning system based on KNN algorithm, aimed at students haven’t finished the course of time can be completed by yourself some predict their courses by chance. In this paper, the basic principle of KNN algorithm is briefly introduced, and the course warning system is modified by Manhattan distance with added weights. This paper briefly describes the basic framework of this model and introduces the application of KNN algorithm in this model. Through a large number of basic experimental data to test the training, using figures to show, finally get the curriculum early warning system model, to achieve the effect of curriculum early warning.

scholarly journals Pengaruh Likuiditas, Profitabilitas dan Leverage terhadap Prediksi Financial Distress

2019 ◽  
Vol 6 (01) ◽  
Author(s):  
Rina Erayanti
Keyword(s):  
Early Warning ◽  
Financial Distress ◽  
Financial Management ◽  
Early Warning System ◽  
Stock Exchange ◽  
Warning System ◽  
Business Development ◽  
System Model ◽  
Sustainable Business ◽  
Purposive Sampling

ABSTRACT The importance of financial management as a vital aspect of the company should be considered and managed properly if the company remains to maintain the sustainable business. Development of an early warning system model is needed to anticipate the financial distress, because this model can identify and improve the condition prior to the crisis. This research aims to examine the liquidity (CR, QR), profitability (ROI, ROE), leverage (DER, DAR), the effect of financial distress. The sample used in this research is the company's transportation, infrastructure and utilities sector in Indonesia Stock Exchange (BEI) for the period year 2012-2016. This research uses purposive sampling, which obtained 171 samples of observations from 39 companies. The hypothesis is examined by using regression logistic. The result shows that the ratio of ROI havesignificant effect on the company’s financial distress. While the CR, QR, ROE DER and DAR have no effect on the company’s financial distress. ABSTRAK Pentingnya pengelolaan keuangan sebagai aspek vital perusahaan benar-benar harus diperhatikan dan dikelola dengan baik jika perusahaan tetap untuk dapat menjaga kelangsungan hidup usahanya. Diperlukan pengembangan model sistem peringatan untuk mengantisipasi adanya financial distress, karena model ini dapat digunakan sebagai sarana untuk mengidentifikasikan bahkan untuk memperbaiki kondisi sebelum sampai pada kondisi krisis. Studi ini bertujuan untuk meneliti pengaruh likuiditas (CR, QR), profitabilitas (ROI, ROE), leverage (DER, DAR), terhadap prediksi financial distress pada perusahaan sektor transportasi, infrastruktur dan utilities yang terdaftar di Bursa Efek Indonesia periode tahun 2012-2016. Pengambilan sampel dengan menggunakan purposive sampling dan diperoleh sebanyak 171 sampel observasi dari 39 perusahaan. Pengujian hipotesis dilakukan dengan menggunakan regression logistik. Hasil pengujian hipotesis mununjukkan bahwa variabel ROI berpengaruh signifikan terhadap financial distress perusahaan. Sedangkan variabel CR, QR, ROE, DER dan DAR tidak berpengaruh terhadap financial distress perusahaan.

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