2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)最新文献

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Artificial neural network flood prediction for sungai isap residence 双溪isap住宅洪水人工神经网络预测

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885321

K. C. Keong, M. Mustafa, A. Mohammad, M. Sulaiman, N. Abdullah

{"title":"Artificial neural network flood prediction for sungai isap residence","authors":"K. C. Keong, M. Mustafa, A. Mohammad, M. Sulaiman, N. Abdullah","doi":"10.1109/I2CACIS.2016.7885321","DOIUrl":"https://doi.org/10.1109/I2CACIS.2016.7885321","url":null,"abstract":"A flood is an extremely dangerous disaster that can wipe away an entire city, coastline, and rural area. The flood can cause wide destrotion to property and life that has the supreme corrosive force and can be highly damaging. In order to decrease the damages caused by the flood, an Artificial Neural Network (ANN) model has been established to predict flood in Sungai Isap, Kuantan, Pahang, Malaysia. This model is able to initiate the same brain thinking process and avoid the influence of the predict judgment. In this paper, presentation and comparison that using Bayesian Regularization (BR) back-propagation, Levenberg-Marquardt (LM) back-propagation and Gradient Descent (GD) back-propagation algorithms will be organized and carry out the result flood prediction. The predicted result of the Bayesian Regularization indicates a satisfactory performance. The conclusions also indicate that Bayesian Regularization is more versatile than Levenberg-Marquart and Gradient Descent with that can be backup or a practical tool for flood prediction. Temperature, precipitation, dew point, humidity, sea level pressure, visibility, wind, and river level data collected from January 2013 until May 2015 in the city of Sungai Isap, Kuantan is used for training, validation, and testing of the network model. The comparison is shown on the basis of mean square error (MSE) and regression (R). The prediction by training function Bayesian Regularization back-propagation found to be more suitable to predict flood model.","PeriodicalId":399080,"journal":{"name":"2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121039440","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: 16

Effect of artificial lighting on typhonium flagelliforme for indoor vertical farming 室内垂直养殖中人工照明对鞭毛台风的影响

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885280

S. S. S. Yusof, N. M. Thamrin, M. K. Nordin, A. Yusoff, N. J. Sidik

{"title":"Effect of artificial lighting on typhonium flagelliforme for indoor vertical farming","authors":"S. S. S. Yusof, N. M. Thamrin, M. K. Nordin, A. Yusoff, N. J. Sidik","doi":"10.1109/I2CACIS.2016.7885280","DOIUrl":"https://doi.org/10.1109/I2CACIS.2016.7885280","url":null,"abstract":"Lately, the idea of indoor vertical farming has caught a wide attention throughout the world either for domestic or commercial purposes. This is one of the ideal decisions in modern agriculture technique when the land area for the plantation activities has become the major concern especially in the urban area. However, certain factors must be considered to mimic the actual condition of the outdoor natural environment. One of the critical elements for the plant to grow is the light source. Therefore, the purpose of this project is to study the effects of few artificial lights such as daylight compact fluorescent light (CFL), blue and red colours of light emitter diode (LED), with a wavelength of 475 nm and 650 nm, respectively, towards the height of the plant, chlorophyll content in the leaves, carbon dioxide release as well as their water contains in the leaves of Typhonium Flagelliforme plants. Based on the result obtained in this research, the blue light promotes and enhances the height of the plant as well as contains the most water in the leaves. Meanwhile, the red light encourages the production of the chlorophyll in the leaves. However, the red LED emits more carbon dioxide compared to others","PeriodicalId":399080,"journal":{"name":"2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127764444","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: 8

Power energy management strategy of micro-grid system 微电网系统电能管理策略

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885298

M. Yusof, A. Z. Ahmad

引用次数: 5

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