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Annals of Mathematical Modeling
Published by Research and Social Study Institute
ISSN : 72157822     EISSN : 72157822     DOI : 10.33292
Core Subject : Science, Education,
Computer Science & IT Mathematics
nnals of Mathematical Modeling integrates authoritative reports on current mathematical, articles cover a wide range of topics, including mathematical analyses, probability, statistics, cybernetics, algebra, geometry, mathematical physics, wave propagation, stochastic processes, boundary value problems, linear operators, and number and function theory. The journal is a valuable resource for pure and applied mathematicians, statisticians, systems theorists and analysts, and information scientists.
Arjuna Subject : Matematika - Matematika Komputer
Articles 24 Documents
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Lung cancer classification based on support vector machine-recursive feature elimination and artificial bee colony Alhadi Bustamam; Zuherman Rustama; Selly A. A. K; Nyoman A. Wibawa; Devvi Sarwinda; NadyaAsanul Husna
Annals of Mathematical Modeling Vol 3, No 1 (2021)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v13i1.71

Abstract

Early detection of cancerous cells can increase survival rates for patients by more than 97%. Microarray data, used for cancer classification, are comp osed of many thousands of features and from tens to hundreds of instances. Handling these huge datasets is the most imp ortant challenge in data classification. Feature selection or reduction is therefore an essential task in data classification. We prop ose a cancer diagnostic to ol using a supp ort vector machine for classifier and feature selection. First, we use supp ort vector machine-recursive feature elimination to prefilter the genes. This was enhanced with the artificial b ee colony algorithm. We ran four simulations using Ontario and Michigan lung cancer datasets. This approach provides higher classification accuracy than those without feature selection, supp ort vector machine-recursive feature elimination, or the artificial b ee colony algorithm. The accuracy of a supp ort vector machine using a feature selection-based recursive feature elimination metho d combined with the artificial b ee colony algorithm reached 98% with 100 b est features for the Michigan lung cancer dataset and 97% with 70 b est features for the Ontario lung cancer dataset. SVM with RFE-ABC as the feature selection metho d gives us an accurate result to diagnose Lung cancer using microarray data.
Research on Regional Economic Development of Guangxi Based on Multiple Statistic Analysis Jian Xin; Weizhang Lai
Annals of Mathematical Modeling Vol 3, No 1 (2021)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v13i1.113

Abstract

Economic development is a prerequisite for social stability and development. However, the regional economic development in various regions of our country is unbalanced, especially in the western region. As one of the minority autonomous regions in western of my country, Guangxi Province is undoubtedly of great practical significance to study its regional economic development. In this context, this paper is based on 8 economic indicators and related economic data of 14 cities in Guangxi Province in 2018, and is based on the theory of dimensionality reduction methods and cluster analysis, using principal component analysis (PCA) and hierarchical clustering methods to assess the comprehensive level of Guangxi’s economic development. The result shows that most cities' economic development in Guangxi Province is great. However, there are signature differences in economic development between urban areas.
Heat transfer of thin-film Casson hybrid nanofluid flow across an unsteady stretching sheet Nur Ilyana Kamis; Md Faisal Md Basir; Taufiq Khairi Ahmad Khairuddin; Lim Yeou Jiann
Annals of Mathematical Modeling Vol 3, No 1 (2021)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v13i1.100

Abstract

Hybrid nanoparticles copper andalumina effect on the heat transfer of thin-filmblood flow toward an unsteady permeablestretching sheet is studied. The influence ofsuction is considered. The governing partialdifferential equations together with boundaryconditions are reduced into the set of ordinarydifferential equations by implementing thesimilarity transformations. The Keller-boxmethod is used to solve the momentum and heatequations. The characteristics of the blood flowand heat transfer under the effect ofunsteadiness parameter, nanoparticles volumefraction, Casson parameter, and intensity ofsuction for different thin-film thickness arediscussed. The numerical results of the velocityand temperature profiles are graphicallydisplayed. The physical interest such as thelocal skin friction and Nusselt number aredepicted in a tabular form.
Cluster analysis of type II diabetes mellitus patients with the fuzzy c-means method Simeftiany Indrilemta Lomo; Endang Darmawan; Sugiyarto Sugiyarto
Annals of Mathematical Modeling Vol 3, No 1 (2021)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/amm.v1i1.102

Abstract

Cluster analysis has been widely used in the fields of mathematics and health sciences. This study aims to classify distance-based data which are divided into several clusters. Accurate prediction from the outcome or survival rate of diabetic patients can be the key for the stratification of prognosis and therapy. A retrospective study of 447 medical record data of type II diabetes mellitus patients aged 18 years old or above and were hospitalized in the PKU Muhammadiyah Gamping Hospital from 2015-2019. Clustering is using the PCA-Fuzzy C-Means method based on patients’ survival status, demographic characteristics, therapy, and blood glucose (BG) levels. Clustering evaluation by Davies Bouldin Index (DBI). Data analysis is using Jupyter Notebook programme. Cluster formation are first cluster consists of 171 members, second cluster consists of 9 members, third cluster consists of 267 members with DBI 2,2645. 401 patients (89,7%) were recorded as alive and 46 patients (10,3%) were recorded as dead. A total of 447 patients: 54,1% were male; 90,6% were ≥ 45 years old; 66,4% has comorbidities; 51,7% had BG level of more than 200 mg/dl, and 57,7% received combination insulin+oral antidiabetic therapy.

Page 3 of 3 | Total Record : 24

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