Prediction Insolvency of Insurance Companies Using Random Forest

analysis of ruin probability for insurance companies using markov chain

در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...

Genetic programming for the prediction of insolvency in non-life insurance companies

Prediction of non-life insurance companies insolvency has arised as an important problem in the 6eld of 6nancial research, due to the necessity of protecting the general public whilst minimizing the costs associated to this problem, such as the e7ects on state insurance guaranty funds or the responsibilities for management and auditors. Most methods applied in the past to predict business failu...

Insolvency Prediction of Irish Companies Using Backpropagation and Fuzzy ARTMAP Neural Networks

Prediction of maximum surface settlement caused by earth pressure balance shield tunneling using random forest

Due to urbanization and population increase, need for metro tunnels, has been considerably increased in urban areas. Estimating the surface settlement caused by tunnel excavation is an important task especially where the tunnels are excavated in urban areas or beneath important structures. Many models have been established for this purpose by extracting the relationship between the settlement a...

Software Fault-proneness Prediction using Random Forest

Many metric-based classification models have been developed and applied to software fault-proneness prediction. This paper presents a novel prediction model using Random Forest classifier. Random Forest (RF) can be a promising candidate for software quality prediction because it is one of the most accurate classification algorithms available and has strengths in noise handling and efficient run...