scholarly journals ON ONE APPROACH OF FORECASTING NATURAL DISASTERS WITH THE SYSTEM OF PATTERN RECOGNITION WITH LEARNING

World Science ◽  
2021 ◽  
Author(s):  
Nelly Tkemaladze ◽  
Giorgi Mamulashvili
Keyword(s):  
Pattern Recognition ◽  
Initial Data ◽  
Natural Disasters ◽  
Natural Disaster ◽  
Data Bases ◽  
The Third ◽  
Using Data ◽  
And Control ◽  
Fixed Region ◽  
The Given

There are a number of recognition problems in different fields that can be solved with the system of pattern recognition with learning – SPRL elaborated by us. The problem of forecasting natural disasters (floods, mudslides) in the given year, the fixed region, and the period belongs to it. To solve it, it is set in the terms of pattern recognition with learning according to which it is necessary to pre-determine the learning descriptions in the same region of the previous years using data of the previous 12 months of the period. From learning descriptions, firstly are separated control descriptions, then the variants of learning and learning recognizable descriptions. Besides, it is necessary to determine descriptions in year, in the same region using data of the same previous period of the (the first model). After transformation and increasing the informativity of the learning descriptions, the knowledge and data bases are determined for learning recognizable and control descriptions in relation to the variants and classes (the second model). Using them, one decision is made on belonging to the respective class for learning recognizable descriptions, but for control descriptions – the primary decisions according to the number of variants, and then on their basis – one decision. Exactly according to the results of the recognition of control descriptions a decision is made on the occurrence (non-occurrence) of a natural disaster in the same region and period (the third model). The article discusses the arguments related to this fact. This model considers the correction of data bases with respect to variants and classes, also, defines the effectiveness of working of the SPRL and its detector of trust. Considering the specifics of forecasting, the initial data of at least 5 years are required to select the best knowledge and data bases with the use of which a disaster should be forecasted.

scholarly journals ON THE METHOD OF DETERMINING LEARNING DESCRIPTIONS TO FORECAST NATURAL DISASTERS WITH THE PATTERN RECOGNITION SYSTEM

World Science ◽  
2020 ◽  
Vol 1 (5(57)) ◽  
pp. 24-30
Author(s):  
Nelly Tkemaladze ◽  
Violeta Jikhvashvili ◽  
Giorgi Mamulashvili
Keyword(s):  
Pattern Recognition ◽  
Natural Disasters ◽  
Real Data ◽  
Recognition System ◽  
Learning Model ◽  
Data Bases ◽  
Initial Information ◽  
Pattern Recognition System ◽  
Parameter Values ◽  
Fixed Region

To forecast natural disasters (floods, mud-slides) in the fixed region and in period T0 with SPRL – the System of Pattern Recognition with Learning (elaborated by us) it is necessary to have the data of the previous 12 months of period T0 and learning descriptions (LDs). To identify this latter, the fact of occurrence or non-occurrence of disasters in the same region and the period T0 should be known in other years and also, the above mentioned 12- month date for each year. Determining LDs based on them is the aim of the article. For this purpose, the method which will be included in the first model of the SPRL is elaborated. The SPRL comprises: 1) preliminary elaboration of the initial information, 2) learning and 3) recognition models. This system is implemented on a PC. It is verified on the basis of the real data to recognize objects of different classis. Primary, additional and formal additional parameters are determined in the method given in the article. On the basis of their values in correlation with the aforementioned 12 months two matrices are determined. The first of them corresponds to the fact of occurrence of disasters and the second one – of non-occurrence. By using these parameter values given in these matrices LDs will be determined. The best LDs will be given to the learning model of the SPRL for transformation and increasing of informativity. Based on the LDs obtained after the transformation, the learning model will make knowledge and data bases.

Risk assessment and comparison of regional natural disasters in China using clustering

2020 ◽  
Vol 14 (3) ◽  
pp. 349-357
Author(s):  
Ning Chen ◽  
Yingchao Ma ◽  
Chaosheng Tang ◽  
An Chen ◽  
Xiaohui Yao
Keyword(s):  
Natural Disasters ◽  
Natural Disaster ◽  
Hybrid Approach ◽  
Disaster Risk ◽  
Second Stage ◽  
The Past ◽  
Variation Patterns ◽  
The World ◽  
Regional Risk ◽  
The Given

Natural disaster that contributes to the economic crisis all over the world has a crucial role in emergency management. The assessment of regional risk to natural disasters is normally studied as a multi-criteria decision making (MCDM) problem in the literature. However little effort was devoted into the comparison of temporary disaster risk of regions. In this paper, a hybrid approach is proposed integrating MCDM and clustering for evaluating and comparing the regional risk to natural disasters. Our two-stage method is applied to thirty-one Chinese regions over the past two consecutive years. In the first stage MCDM is used to prioritize the regions yearly yielding a set of risk vectors over the given period. In the second stage, K-means clustering is applied to divide the regions into a number of clusters characterized by different risk variation patterns. The derived patterns reveal the variation of regions in perspective of natural disaster risk and therefore offer valuable suggestions for disaster risk reduction.

scholarly journals BENCANA ALAM DAN BI RATE TERHADAP PENGHIMPUNAN DANA ZIS DENGAN INFLASI SEBAGAI VARIABEL INTERVENING PADA BAZNAS INDONESIA

2021 ◽  
Vol 8 (1) ◽  
pp. 32
Author(s):  
Halimatussa'idah Halimatussa'idah ◽  
Ari Prasetyo
Keyword(s):  
Path Analysis ◽  
Natural Disasters ◽  
Natural Disaster ◽  
Analytical Method ◽  
Quantitative Approach ◽  
The Third ◽  
Muslim Communities ◽  
The Impact

ABSTRAKIndonesia memiliki jumlah masyarakat muslim yang besar. Maka dari itu, besarnya penerimaan ZIS harus dimaksimalkan dan agar dapat membantu perekonomian negara. Penelitian ini bertujuan untuk menganalisis dampak bencana alam, BI Rate terhadap penghimpunan dana Zakat, Infaq dan Shadaqah (ZIS) di BAZNAS Indonesia dari Januari 2016 hingga Desember 2019. Penelitian ini menggunakan pendekatan kuantitatif dan metode analisis yang digunakan dalam penelitian ini adalah analisis jalur. Hasil penelitian ini menemukan bahwa BI Rate berpengaruh positif dan signifikan, bencana alam berpengaruh negatif dan signifikan, Inflasi berpengaruh negatif dan signifikan terhadap ZIS. Faktor yang paling berpengaruh terhadap ZIS adalah inflasi. Kedua, bencana alam dan ketiga adalah BI Rate.Kata Kunci: Zakat Infaq Shadaqah (ZIS), BI Rate, Inflasi, Bencana Alam, Analisis Jalur. ABSTRACTIndonesia has a large number of Muslim communities. The amount of ZIS revenue should be maximized and can help the country's economy. This research is to analyze the impact of natural disaster, BI Rate towards collection of Zakat, Infaq and Shadaqah fund at BAZNAS Indonesia from January 2016 to December 2019. This research uses quantitative approach and the analytical method used in this study is path analysis. This research found that BI Rate has positive and significant, natural disaster has negative and significant, Inflation has negative and significant towards ZIS. The factor that has the most influence on ZIS is inflation. Second, natural disasters and the third is the BI Rate.Keyword: Zakat Infaq Shadaqah (ZIS), BI Rate, Inflation, Natural Disaster, Path Analysis.

State, Society and Natural Disaster: Cyclone Nargis in Myanmar (Burma)

2009 ◽  
Vol 37 (5) ◽  
pp. 717-737 ◽  
Author(s):  
Donald Seekins
Keyword(s):  
Natural Disasters ◽  
Natural Disaster ◽  
Tropical Cyclones ◽  
Human Security ◽  
The Political ◽  
Political Environment ◽  
State Security ◽  
Negative Factor ◽  
Cyclone Nargis ◽  
And Control

AbstractInternational efforts to provide relief to areas struck by natural disasters, such as tropical cyclones or earthquakes, are usually evaluated in terms of logistical, personnel and technical criteria — how to get needed supplies and services to affected populations quickly and effectively. These criteria are, of course, essential. However, the case of Cyclone Nargis, which struck the Ayeyarwady (Irrawaddy) Delta and other parts of southern Myanmar (Burma) on 2–3 May 2008, shows that the political environment can be a significant negative factor in aid delivery. Fearful of popular unrest and foreign influence, the Myanmar government tried to limit and control the provision of relief to an estimated 2.4 million cyclone survivors. It may be concluded from this experience that governments, such as Myanmar's, with limited popular support and legitimacy are likely to prioritise state security over human security, even in cases of extreme humanitarian need.

scholarly journals Analisis Cluster Intensitas Kebencanaan di Indonesia Menggunakan Metode K-Means

2019 ◽  
Vol 2 (2) ◽  
pp. 137
Author(s):  
Hafiz Yusuf Heraldi ◽  
Nabila Churin Aprilia ◽  
Hasih Pratiwi
Keyword(s):  
Natural Disasters ◽  
Natural Disaster ◽  
Disaster Management ◽  
Disaster Response ◽  
Soil Hydrology ◽  
The Third ◽  
Central Java ◽  
The World ◽  
The Government ◽  
Natural Disaster Management

<p>Indonesia is one of the most prone countries to natural disasters in the world because of the climate, soil, hydrology, geology, and geomorphology. There are many different natural disasters, but the three most common natural disasters in Indonesia are flood, landslide, and tornado. This research aimed to cluster the provinces in Indonesia based on the flood, landslide, and tornado’s intensity in 2018. The results of clustering by K-Means method in this research divided the provinces in Indonesia into four clusters. The second cluster contained West Java, Central Java, and Bali, the third cluster contained DKI Jakarta, the fourth cluster contained DI Yogyakarta, and the first cluster contained the other 29 provinces. The result of this research hopefully can help the government in order to make decision and improve the natural disaster management system, such as preparedness, disaster response, and disaster recovery based on the most common disaster in each province. Furthermore, the society is expected to be more aware on natural disaster management based on the most common natural disaster in province that they lived.</p><p><strong>Keywords : </strong>natural disaster, cluster, k-means</p>

Analisa Data Bencana Alam Untuk Prediksi Dampak Yang Ditimbulkan Dengan Algoritma J48 (Studi Kasus : Palang Merah Indonesia)

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Dewi Shintya Lumbansiantar
Keyword(s):  
Data Mining ◽  
Natural Disasters ◽  
Natural Disaster ◽  
Volcanic Eruptions ◽  
Red Cross ◽  
Natural Event ◽  
Disaster Data ◽  
Mining Methods ◽  
Using Data ◽  
The Impact

Natural disaster is a natural event that is difficult to avoid and difficult to estimate the exact impact of natural disasters that can be fatalities, social environment, propety, losses, even distrubance to the community even though it is very likely to occur. As for the disasters that often occur in Indonesia including floods, landslides, tsunamis, earthquakes and volcanic eruptions. The lack of relief supplies provided by the Indonesian Red Cross (PMI) was caused by the absence of data on the need for assistance provided. Therefore it is necessary to analyze natural disaster data that has happened before to be used to predict the impact caused by natural disasters. Prediction of the amount of assistance needed can be done using data mining techniques, therefore this study amis to analyzenatural disaster data using data mining methods using the J48 algorithm. To analyze natural disastr data for prediction of the impact can be used by rapidminer testing so that the results can be in the form of a decision tree.Keywords: Data Mining, Natural Disaster Data, J48 Algorithm

When Mother Earth Rises Up

2013 ◽  
Vol 44 (4) ◽  
pp. 271-277 ◽  
Author(s):  
Simona Sacchi ◽  
Paolo Riva ◽  
Marco Brambilla
Keyword(s):  
Free Will ◽  
Natural Disasters ◽  
Natural Disaster ◽  
Mental States ◽  
Disaster Victims ◽  
Willingness To Help ◽  
Mother Earth

Anthropomorphization is the tendency to ascribe humanlike features and mental states, such as free will and consciousness, to nonhuman beings or inanimate agents. Two studies investigated the consequences of the anthropomorphization of nature on people’s willingness to help victims of natural disasters. Study 1 (N = 96) showed that the humanization of nature correlated negatively with willingness to help natural disaster victims. Study 2 (N = 52) tested for causality, showing that the anthropomorphization of nature reduced participants’ intentions to help the victims. Overall, our findings suggest that humanizing nature undermines the tendency to support victims of natural disasters.

Pattern Recognition in Histo-Pathology: Basic Considerations

1982 ◽  
Vol 21 (01) ◽  
pp. 15-22 ◽  
Author(s):  
W. Schlegel ◽  
K. Kayser
Keyword(s):  
Pattern Recognition ◽  
Graph Theory ◽  
Normal Tissue ◽  
Diagnostic Procedures ◽  
Minimal Distance ◽  
Malignant Growth ◽  
Colon Tissue ◽  
First Results ◽  
Tissue Structures ◽  
The Given

A basic concept for the automatic diagnosis of histo-pathological specimen is presented. The algorithm is based on tissue structures of the original organ. Low power magnification was used to inspect the specimens. The form of the given tissue structures, e. g. diameter, distance, shape factor and number of neighbours, is measured. Graph theory is applied by using the center of structures as vertices and the shortest connection of neighbours as edges. The algorithm leads to two independent sets of parameters which can be used for diagnostic procedures. First results with colon tissue show significant differences between normal tissue, benign and malignant growth. Polyps form glands that are twice as wide as normal and carcinomatous tissue. Carcinomas can be separated by the minimal distance of the glands formed. First results of pattern recognition using graph theory are discussed.

UPAYA MENINGKATKAN AKTIVITAS DAN HASIL BELAJAR MAHASISWA MELALUI PENERAPAN MODEL PEMBELAJARAN INKUIRI PADA MATA KULIAH KONSEP DASAR IPA 2 DI PROGRAM STUDI PENDIDIKAN GURU SEKOLAH DASAR TAHUN AKADEMIK 2013/2014

2014 ◽  
Vol 3 (1) ◽  
pp. 23
Author(s):  
Mahmud Alpusari
Keyword(s):  
Initial Data ◽  
Learning Outcomes ◽  
Inquiry Learning ◽  
Learning Activities ◽  
Simple Experiment ◽  
Competency Based ◽  
Basic Concepts ◽  
Using Data ◽  
The University ◽  
Daily Test

In line with the competency-based curriculum at the University of Riau, the effort to improvelearning basic concepts of science 2 courses puts emphasis on understanding the concept ofmatter, which is based on students' learning activities through scientific inquiry.Implementation of action research consists of two cycles in PGSD JIP University of Riau onthe odd semester of 2013/2014 with 55 third semester students. Based on the research results,lecturing process by applying the model of inquiry learning, students’ activity increased inwhich in the first cycle all activities are good category except activity I and II are faircategory. Meanwhile students’ activity in first and fourth in cycle II is good category, andvery good category in second, third, fifth, and sixth activity. Temporarily student’s learningoutcomes increased from pre-tests with an average65.45 into 77,0 in daily test I and 77.45onthe daily test II. Improvement from initial data to the first cycle was 11.55, while the datafrom the beginning to the second cycle increased 12 points. In general the improvement ofstudents’learning is possible because the learning model used is inquiry learning so thatlearning becomes active which centered into students by presenting a problem, then studentsare asked to carry out a simple experiment using equipment and tools, using data, arrangingreports, communicating the results of observations based on concepts and learned principles.Keywords: Inquiry, students’ activity, learning outcomes.

THE EFFECT OF APPLYING DEMONSTRATION METHOD ON STUDENTS’ ACHIEVEMENT IN SPEAKING SKILL AT THE THIRD GRADE OF SMK PAB 3 MEDAN ESTATE

2015 ◽  
Vol 4 (2) ◽  
Author(s):  
Meryanti Napitupulu And Anni Holila Pulungan
Keyword(s):  
High School ◽  
Control Group ◽  
Vocational High School ◽  
Control Groups ◽  
Speaking Test ◽  
The Third ◽  
Speaking Skill ◽  
The Subject ◽  
And Control ◽  
Experimental Group

This study was conducted as an attempt to discover the effect of applying Demonstration Method on students’ achievement in speaking skill. It was an experimental research. The subject was students of Grade XII, Vocational High School (Sekolah Menengah Kejuruan: SMK), which consisted of 79 students. The research was divided into two groups: experimental and control groups. The instrument used to collect the data was speaking test. To obtain the reliability of the test, the writer applied Kuder Richardson 21 formula. The result of the reliability was 0.7, and it was found that the test was reliable. The data were analyzed by using t-test formula. The analysis showed that the scores of the students in the experimental group were significantly higher than the scores of the students in the control group at the level of significant m = 0.05 with the degree of freedom (df) 77, t-observed value 8.9 > t-table value 1.99. The findings indicate that using Demonstration Method significantly affected the students’ achievement in speaking skill. So, English teachers are suggested to use Demonstration Method in order to improve students’ achievement in speaking skill.

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