Casing life prediction using Borda and support vector machine methods
نویسندگان
چکیده
منابع مشابه
Bubble Pressure Prediction of Reservoir Fluids using Artificial Neural Network and Support Vector Machine
Bubble point pressure is an important parameter in equilibrium calculations of reservoir fluids and having other applications in reservoir engineering. In this work, an artificial neural network (ANN) and a least square support vector machine (LS-SVM) have been used to predict the bubble point pressure of reservoir fluids. Also, the accuracy of the models have been compared to two-equation stat...
متن کاملsiRNA Efficiency Prediction Using Support Vector Machine
RNA Interference (RNAi) is a selective gene silencing mechanism initiated by double stranded RNA (dsRNA). The short RNA species called siRNAs are formed from dsRNA, which can degrade the messenger RNA (mRNA). This knockdown prevents mRNA from producing amino acid sequences which are responsible for gene expression. Thus siRNA alters the regulatory role of mRNA during gene expression by translat...
متن کاملSoftware Defect Prediction using Support Vector Machine
developing a defect free software system is very difficult and most of the time there are some unknown bugs or unforeseen deficiencies even in software projects where the principles of the software development methodologies were applied care-fully. Due to some defective software modules, the maintenance phase of software projects could become really painful for the users and costly for the ente...
متن کاملMonthly rainfall Forecasting using genetic programming and support vector machine
Rainfall and runoff estimation play a fundamental and effective role in the management and proper operation of the watershed, dams and reservoirs management, minimizing the damage caused by floods and droughts, and water resources management. The optimal performance of intelligent models has increased their use to predict various hydrological phenomena. Therefore, in this study, two intelligent...
متن کاملCarbon Monoxide Prediction in the Atmosphere of Tehran Using Developed Support Vector Machine
Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily C...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Petroleum Science
سال: 2010
ISSN: 1672-5107,1995-8226
DOI: 10.1007/s12182-010-0087-8