The estimation of an increase in sea level with sufficient warning time is important in low-lying regions, especially in the east coast of Peninsular Malaysia (ECPM). This study primarily aims to investigate the validity and effectiveness of the support vector machine (SVM) and genetic programming (GP) models for predicting the monthly mean sea level variations and comparing their prediction accuracies in terms of the model performances. The input dataset was obtained from Kerteh, Tioman Island, and Tanjung Sedili in Malaysia from January 2007 to December 2017 to predict the sea levels for five different time periods (1, 5, 10, 20, and 40 years). Further, the SVM and GP models are subjected to preprocessing to obtain optimal performance. The tuning parameters are generalized for the optimal input designs (SVM2 and GP2), and the results denote that SVM2 outperforms GP with R of 0.81 and 0.86 during the training and testing periods, respectively, at the study locations. However, GP can provide values of 0.71 and 0.79 for training and testing, respectively, at the study locations. The results show precise predictions of the monthly mean sea level, denoting the promising potential of the used models for performing sea level data analysis.
This research is to investigate the properties of compressed building bricks producedfrom Cameron Highlands reservoir sediment. The particle size distribution of the sediments are graded as silt and sand. The sediments used were as total replacement of the normal soils used in the compressed soil bricks. This paper presents the compilation of experimental brick properties; compressive strength, water absorption, microstructure and heavy metal leachingof the compressed sediment bricks. The experimental results shows that increasing use of reservoir sediments decrease the compressive strength andincrease the water absorption. The heavy metal concentrations of the leachates from the leaching test are all within the regulatory limits. The optimum mix is derives from the compressive strength and the water absorption in which in this research is Mix 4, 70% sedimenta, 20% sedimentb and 10% cement,complying with ASTM C129 – Non Load Bearing Bricks [1].
Electrical companies generate electricity mainly from two major types of plant; hydroelectric plants and thermal plants. Hydroelectric is the term referring to electricity generated by hydropower; the production of electrical power through the use of the gravitational force of falling or flowing water through dams operation. The sedimentation of such dams over years will cause large capacity losses of the dams. Thermal plants generate electricity through coal-fired power plants which produce millions tons of fly ash yearly. This fly ash accumulates rapidly and causes enormous problems of disposal. Therefore, the research work presented in this paper is dealing with utilizing reservoir sediment and fly as to form brick under pressure. Sediment brick can be produced as a load bearing brick with compressive strength is greater than 7 N/mm2.
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