2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)最新文献_第7页

Forecasting Thailand’s Precipitation with Cascading Model of CNN and GRU 用CNN和GRU级联模式预测泰国降水

2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2019-10-01 DOI: 10.1109/ICITEED.2019.8929975

Fuenglada Manokij, Kanoksri Sarinnapakorn, P. Vateekul

{"title":"Forecasting Thailand’s Precipitation with Cascading Model of CNN and GRU","authors":"Fuenglada Manokij, Kanoksri Sarinnapakorn, P. Vateekul","doi":"10.1109/ICITEED.2019.8929975","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929975","url":null,"abstract":"Precipitation prediction is necessary to use in water management, especially in Thailand, it can be applied for various ways, such as flood warning, agriculture planning, etc. There are many prior attempts to forecast rainfall from the rain-gauge station. Some deployed traditional machine learning approaches: ARIMA, k-NN, etc. Recently, deep learning approach has shown promising results in this task. However, the accuracy is still limited since the raining period throughout the year in Thailand is very scarce, so most rainfall amount is zero. In this paper, we propose to cascade two deep learning networks to tackle this problem: one is a classification model to classify whether it rains or not, and the other is a regression model to predict rainfall amount. Our network is a combination of CNN and GRU, where CNN aims to capture relationship between various sensors and GRU aims to capture time-series information. Furthermore, we also perform multi-step forecasting by applying a rolling mechanism that uses the predicted rainfall and involved features to predict the next 6 steps. The experiment was conducted on hourly rainfall dataset for 6 years (2013-2018) provided from the public government sector in Thailand. We use RMSE as performance metric to evaluate three periods of rainfall: Overall, Rain, and non-rain periods and the results show that our cascading model is the winner with only 4.53% in term of RMSE which is the average percentage of difference from over all regions.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"163 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78557633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

4-ary Odor-Shift Keying Using Multi-channel Olfactory Display 使用多通道嗅觉显示的4-ary气味移位键控

2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2019-10-01 DOI: 10.1109/ICITEED.2019.8930003

Sumek Wisayataksin, Panupong Angkasuwan, Y. Ariyakul

引用次数: 0

Multithresholding Approach for Segmenting Plasmodium Parasites 疟原虫分段的多阈值法

2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2019-10-01 DOI: 10.1109/ICITEED.2019.8929995

Hanung Adi Nugroho, A. Fatan D. Marsiano, Khampaserth Xaphakdy, Phounsiri Sihakhom, Eka Legya Frannita, Rizki Nurfauzi, E. Elsa Herdiana Murhandarwati

{"title":"Multithresholding Approach for Segmenting Plasmodium Parasites","authors":"Hanung Adi Nugroho, A. Fatan D. Marsiano, Khampaserth Xaphakdy, Phounsiri Sihakhom, Eka Legya Frannita, Rizki Nurfauzi, E. Elsa Herdiana Murhandarwati","doi":"10.1109/ICITEED.2019.8929995","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929995","url":null,"abstract":"Malaria has become one of the deadliest diseases in the world. The main method in diagnosing malaria is manually conducted by pathologists using a microscope. This process is time-consuming and prone to error due to human factor. These facts encourage the development of system that consistently yielded more objective results regardless of the condition on the field. In this research work, a novel method to segment infected erythrocytes using threshold and morphological is proposed. The proposed method was tested in a database consisting of 30 images with varying condition. The experimental results showed that the proposed method achieved 96.74 ± 0.7075 %, 76.77 ± 2.1441 %, 99.74 ± 0.1397 %, 97.84 ± 1.2514 % and 96.61 ± 0.8021 % of accuracy, sensitivity, specificity, prediction value positive and prediction value negative, respectively. In conclusion, the proposed method provides a consistent result for segmenting parasite in infected erythrocytes image. This result indicates that this proposed scheme is proper to assist the pathologists in detecting Plasmodium parasites.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"59 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90625216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Modified Binary Flower Pollination Algorithm: A Fast and Effective Combination of Feature Selection Techniques for SNP Classification 一种改进的二元花授粉算法:快速有效地结合特征选择技术进行SNP分类

2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2019-10-01 DOI: 10.1109/ICITEED.2019.8929963

Wanthanee Rathasamuth, Kitsuchart Pasupa

{"title":"A Modified Binary Flower Pollination Algorithm: A Fast and Effective Combination of Feature Selection Techniques for SNP Classification","authors":"Wanthanee Rathasamuth, Kitsuchart Pasupa","doi":"10.1109/ICITEED.2019.8929963","DOIUrl":"https://doi.org/10.1109/ICITEED.2019.8929963","url":null,"abstract":"Single nucleotide polymorphism (SNP) is a genetic trait responsible for the differences in the characteristics of individuals of a living species. Machine learning has been brought in to classify swine breed according to their SNPs. However, since the number of samples (number of pigs sampled) is usually much smaller than the number of features (SNPs) to classify, there may occur an overfitting problem. Therefore, some feature selection techniques were applied to the entire SNPs to reduce them to a much smaller number of most significant SNPs to be used in the classification. In this study, we used information gain in combination with binary flower pollination algorithm for feature selection as well as a cut-off-point-finding threshold for specifying a 0 or 1 value for a position in the solution vector and a GA bit-flip mutation operator. We called it Modified-BFPA. The classifier was SVM. Evaluated against a few other feature selection techniques, our combination of techniques was, at the very least, competitive to those. It selected only 1.76 % of most significant SNPs from the entire set of 10,210 SNPs. The SNPs that it selected provided 95.12 % classification accuracy. Moreover, it was fast: an average of 1.60 iterations in combination with SVM to find a set of best SNPs that provided the highest classification accuracy.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"71 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79052468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Toward a Common System Architecture for Knowledge Mapping 面向知识映射的通用系统体系结构

2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2019-10-01 DOI: 10.1109/ICITEED.2019.8929935

Shidiq Al Hakim, D. I. Sensuse

引用次数: 2