Please use this identifier to cite or link to this item:
https://ptsldigital.ukm.my/jspui/handle/123456789/457813Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Anuar Kasa, Ir. | - |
| dc.contributor.author | Tarig Mohamed Elamin Elnur Ahmed (P44301) | - |
| dc.date.accessioned | 2023-09-12T09:13:47Z | - |
| dc.date.available | 2023-09-12T09:13:47Z | - |
| dc.date.issued | 2011-12-05 | - |
| dc.identifier.other | ukmvital:122303 | - |
| dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/457813 | - |
| dc.description | Modern software makes it possible to analyze and deal with more complex problems of slopes. It can now deal with different layers, different linear and non-linear models of shear strength, various conditions of pore-water pressure, reinforcement structure, concentrated loads and various types of slip surface shape. However, that software is quite expensive and requires input from engineers especially time and energy to use it. To help new users and young engineers make decision, safety factors were predicted using Adaptive Neuro Fuzzy Inference System (ANFIS) and Multiple Linear Regression (MLR). An ANFIS model that could calculate the safety factors faster and cheaper was created. Fuzzy inference is the process of formulating the mapping from a given input to an output using fuzzy logic. The mapping then provides a basis from which decisions can be made, or patterns discerned. Fuzzy logic which is based on natural language is conceptually easy to understand, flexible, and tolerant of imprecise data. It can model nonlinear functions of arbitrary complexity, can be built on top of the experience of experts and can be blended with conventional control techniques. From previous studies, ANFIS was proven to produce better results compared with other methods, i.e. MLR and Artificial Neural Network (ANN). Data used in this study were 366 various designs of slope. Those designs were created by using Slope/W which calculated factors of safety using various limit equilibrium methods (LEM) such as Bishop, Spencer and Morgenstern-Price. The input parameters consisted of height of slope, H (1–10 m), unit weight of slope material, γ (15-22 kN/m3 ), angle of slope, θ (11.31q-78.69q), coefficient of cohesion, c (0-50 kN/m2 ) and internal angle of friction, I (20q-40q) and the output parameter is the factor of safety. To build the fuzzy inference system, 243 rules were used at 60 epochs. The number of membership function for the any input was three and the type of membership function for output was linear. ANFIS obtained regression square (R2 ) of one for Bishop, one for Janbu, one for Morgenstern-Price and one for Ordinary. The result showed that ANFIS could predict the safety factor with high accuracy and close to the target data. Prediction using MLR obtained regression square of 0.4597 for Bishop, 0.4496 for Janbu, 0.4600 for Morgenstern-Price and 0.4565 for Ordinary. The result showed that MLR could predict the safety factors with low accuracy compared with ANFIS. A Graphical User Interface (GUI) program which displayed four different plots in a single window for the LEMs was built to present the relationship between the input and the output parameters.,Master of Engineering,Certification of Master's / Doctoral Thesis" is not available" | - |
| dc.language.iso | eng | - |
| dc.publisher | UKM, Bangi | - |
| dc.relation | Faculty of Engineering and Built Environment / Fakulti Kejuruteraan dan Alam Bina | - |
| dc.rights | UKM | - |
| dc.subject | Slopes (Soil mechanics) -- Stability | - |
| dc.subject | Soil mechanics | - |
| dc.subject | Engineering geology | - |
| dc.subject | Universiti Kebangsaan Malaysia -- Dissertations | - |
| dc.subject | Dissertations, Academic -- Malaysia | - |
| dc.title | Determination of safety factor for slopes using adaptive neuro fuzzy inference system | - |
| dc.type | theses | - |
| dc.format.pages | 122 | - |
| dc.identifier.callno | TA749.A377 2011 3 tesis | - |
| dc.identifier.barcode | 005604(2021)(PL2) | - |
| Appears in Collections: | Faculty of Engineering and Built Environment / Fakulti Kejuruteraan dan Alam Bina | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_122303+SOURCE1+SOURCE1.0.PDF Restricted Access | 14.74 MB | Adobe PDF |  View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.