صورة الغلاف

Prediction of Soil Pore Water Pressure Using Polynomial Kernel Support Vector Machine

Knowledge in soil pore water pressure is important in slope stability analysis. The fluctuation of soil pore water pressure is mainly affect by the rainfall intensity. The pore water pressure can cause effect on the soil strength. A few problems has been identified in obtaining the pore water pre...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Muhd Hasbi, Muhamad Alif
التنسيق:	Final Year Project
اللغة:	English
منشور في:	Universiti Teknologi PETRONAS 2017
الموضوعات:	TA Engineering (General). Civil engineering (General)
الوصول للمادة أونلاين:	http://utpedia.utp.edu.my/23027/1/FINAL%20DISSERTATION.pdf http://utpedia.utp.edu.my/23027/
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة

Prediction of Soil Pore Water Pressure Using Polynomial Kernel Support Vector Machine
بواسطة: Muhd Hasbi, Muhamad Alif
منشور في: (2017)

Evaluation of low degree polynomial kernel support vector machines for modelling Pore-water pressure responses
بواسطة: Babangida, N.M., وآخرون
منشور في: (2016)

Linear kernel support vector machines for modeling pore-water pressure responses
بواسطة: Yusof, K.W., وآخرون
منشور في: (2017)

PREDICTION OF SOIL PORE WATER PRESSURE RESPONSES TO RAINFALL USING RADIAL BASIS KERNEL FUNCTION
بواسطة: Mohd Anuar, Nurulain Husna
منشور في: (2016)

Modelling Pore Water Pressure Using Sigmoid Kernel Function
بواسطة: Kamarul Bahrin, Nurul Syahirah
منشور في: (2016)

Pore Pressure Analysis In Fine Sediment
بواسطة: SITI NORFARIHA MAT HASBI, SITI
منشور في: (2012)

Soil liquefaction prediction based on bayesian optimization and support vector machines
بواسطة: Zhang, Xuesong, وآخرون
منشور في: (2022)

Prediction of Pore Water-Pressure Using Multiple Linear Regression (MLR)
بواسطة: Abu Bakar, Fatin Amirah
منشور في: (2016)

PREDICTION OF PORE WATER-PRESSURE USING GENERALIZED REGRESSION NEURAL NETWORK
بواسطة: MOHD SAAD, NOR HASWANI
منشور في: (2016)

Prediction of cantilever retaining wall stability using optimal kernel function of support vector machine
بواسطة: Rohaya Alias, وآخرون
منشور في: (2021)

Prediction of pore-water pressure using radial basis function neural network
بواسطة: Mustafa, M.R., وآخرون
منشور في: (2012)

The effect of kernel functions on cryptocurrency prediction using support vector machines
بواسطة: Hitam, Nor Azizah, وآخرون
منشور في: (2021)

The effect of Kernel functions on cryptocurrency prediction using support vector machines
بواسطة: Hitam, Nor Azizah, وآخرون
منشور في: (2022)

The effect of kernel functions on cryptocurrency prediction using support vector machines
بواسطة: Hitam, Nor Azizah, وآخرون
منشور في: (2022)

The effect of kernel functions on cryptocurrency prediction using support vector machines
بواسطة: Hitam, Nor Azizah, وآخرون
منشور في: (2021)

The effect of kernel functions on cryptocurrency prediction using support vector machines
بواسطة: Ismail, Amelia Ritahani, وآخرون
منشور في: (2022)

Effect of Antecedent Conditions on Prediction of Pore-Water Pressure Using Artificial Neural Networks
بواسطة: Mustafa, M.R., وآخرون
منشور في: (2012)

Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall
بواسطة: Mustafa, M.R., وآخرون
منشور في: (2013)

Prediction of ventricular fibrillation using support vector machine
بواسطة: Heng, Wei Wei, وآخرون
منشور في: (2020)

Soil Pore Water Pressure and River Suspended Sediment Modelling using Artificial Neural Networks
بواسطة: Ul Mustafa, Muhammad Raza
منشور في: (2012)

Kernel methods and support vector machines for handwriting recognition
بواسطة: Ahmad A.R., وآخرون
منشور في: (2023)

Effect of antecedent rainfall on pore-water pressure distribution characteristics in residual soil slopes under tropical rainfall
بواسطة: Rezaur R.B., Rezaur, وآخرون
منشور في: (2008)

An application of predicting student performance using kernel k-means and smooth support vector machine
بواسطة: Sajadin, Sembiring
منشور في: (2012)

Fiber fault monitoring for passive optical network using a kernel-based support vector machine
بواسطة: Usman, Auwalu, وآخرون
منشور في: (2021)

Model studies on the effect of deep excavation on pore water pressure and settlement
بواسطة: Mohamed Isa, Mohd. Fairuz
منشور في: (2000)

Study on the variation of pore water pressure with different depth due to rainfall
بواسطة: Mohd Shipah, Nur Athirah
منشور في: (2014)

Evaluation of Landslide Possibility Based on Pore Water Pressure Mechanism and Mitigation
بواسطة: Namdar, Abdoullah
منشور في: (2012)

Pore Pressure Estimation in HPHT Wells
بواسطة: Alias, Abdul Hakim
منشور في: (2011)

Prediction of Pore water Pressure Responses to Rainfall Using Auto Regressive Integrated Moving Average Method (ARIMA)
بواسطة: SATHIVEL, SHALINI
منشور في: (2016)

Pore Pressure Prediction in Shale Gas Field
بواسطة: Hamid, Munawar
منشور في: (2013)

Comparative study between radial basis function and polynomial of support vector regression in predicting flood
بواسطة: Azhari , Farhana
منشور في: (2010)

Speed up grid-search for kernels selection of support vector regression
بواسطة: Ahmad Yasmin, Nur Sakinah, وآخرون
منشور في: (2022)

Speed up grid-search for Kernels selection of support vector regression
بواسطة: Ahmad Yasmin, Nur Sakinah, وآخرون
منشور في: (2022)

Finding kernel function for stock market prediction with support vector regression
بواسطة: Chai, Chon Lung
منشور في: (2006)

Prediction of pore-water pressure using radial basis function neural network
منشور في: (2012)

Water Quality Prediction Model Based Support Vector Machine Model for Ungauged River Catchment under Dual Scenarios
بواسطة: Abobakr Yahya, Abobakr Saeed, وآخرون
منشور في: (2019)

Ozone prediction based on support vector machine
بواسطة: Tanaskuli, M., وآخرون
منشور في: (2020)

Ozone prediction based on support vector machine
بواسطة: Tanaskuli M., وآخرون
منشور في: (2023)

Determination of Unknown Parameters for Pore Pressure Modelling in High Pressure Reservoir
بواسطة: Md Anuar Al-Musadda, Sumaiyah binti
منشور في: (2012)

Hybrid least squares support vector machines for short term predictive analysis
بواسطة: Zuriani, Mustaffa, وآخرون
منشور في: (2017)