Financial distress prediction based on OR-CBR in the principle of k-nearest neighbors

Li, Hui; Sun, Jie; Sun, Bingbing

doi:10.1016/j.eswa.2007.09.038

Cited by 85 publications

(34 citation statements)

References 40 publications

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“…They concluded that the predictive performance of the H2CBR system is promising and also the most preferred hybrid CBR for short-term bank failure prediction of Chinese listed companies is based on the ranking-order preference function. Other examples of this type of comparisons are done by [248][249][250][251][252][253][254][255][256][257][258][259][260][261][262][263][264][265][266]. Table 18 presents the brief results of these comparisons.…”

Section: Financial Prediction and Planningmentioning

confidence: 98%

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

Bahrammirzaee

2010

Neural Comput & Applic

430

192

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Nowadays, many current real financial applications have nonlinear and uncertain behaviors which change across the time. Therefore, the need to solve highly nonlinear, time variant problems has been growing rapidly. These problems along with other problems of traditional models caused growing interest in artificial intelligent techniques. In this paper, comparative research review of three famous artificial intelligence techniques, i.e., artificial neural networks, expert systems and hybrid intelligence systems, in financial market has been done. A financial market also has been categorized on three domains: credit evaluation, portfolio management and financial prediction and planning. For each technique, most famous and especially recent researches have been discussed in comparative aspect. Results show that accuracy of these artificial intelligent methods is superior to that of traditional statistical methods in dealing with financial problems, especially regarding nonlinear patterns. However, this outperformance is not absolute.

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Section: Financial Prediction and Planningmentioning

confidence: 98%

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

Bahrammirzaee

2010

Neural Comput & Applic

430

192

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“…Kim and Han [13] presented a case-indexing method of CBR which utilizes SOM for the prediction of corporate bond rating. Li et al [14] introduced a feature-based similarity measure to deal with financial distress prediction (e.g., bankruptcy prediction) in China. Chang and Lai [15] integrated the SOM and CBR for sales forecasts of newly released books.…”

Section: Introductionmentioning

confidence: 99%

Hepatitis Disease Diagnosis Using Hybrid Case Based Reasoning and Particle Swarm Optimization

Neshat

Sargolzaei

Toosi

et al. 2012

ISRN Artificial Intelligence

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Correct diagnosis of a disease is one of the most important problems in medicine. Hepatitis disease is one of the most dangerous diseases that affect millions of people every year and take man’s life. In this paper, the combination of two methods of PSO and CBR (case-based reasoning) has been used to diagnose hepatitis disease. First, a case-based reasoning method is workable to preprocess the data set therefore a weight vector for every one feature is extracted. A particle swarm optimization model is then practical to assemble a decision-making system based on the selected features and diseases recognized. Many researchers have tried to have a more accurate diagnosis of the disease through the use of various methods. The data used has been taken from the site UCI called hepatitis disease. This database has 155 records and 19 fields. This method was compared with five other classification methods and given the results of the proposed method (CBR-PSO), better results were achieved. The proposed method could diagnose hepatitis disease with the accuracy of 93.25%.

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“…Kim and Han (2001) presented a caseindexing method of CBR which utilizes SOM for the prediction of corporate bond rating. Li et al (2009) introduced a feature-based similarity measure to deal with financial distress prediction (e.g., bankruptcy prediction) in China. Chang and Lai (2005) integrated the SOM and CBR for sales forecasts of newly released books.…”

Section: New Tools In Soft Computingmentioning

confidence: 99%

Forecasting of manufacturing cost in mobile phone products by case-based reasoning and artificial neural network models

2010

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The mobile phone manufacturers in Taiwan have made great efforts in proposing the rational quotations to the international phone companies with the ambition to win the bids by out beating other phone manufacturers. However, there are a lot of uncertainties and issues to be resolved in estimating the manufacturing costs for mobile phone manufacturers. As far as we know, there is no existing model which can be applied directly in forecasting the manufacturing costs. This research makes the first attempt to develop a hybrid system by integrated Case-Based Reasoning (CBR) and Artificial Neural Networks (ANN) as a Product Unit Cost (PUC) forecasting model for Mobile Phone Company. According to the cost formula of the mobile phone and experts' opinions, a set of qualitative and quantitative factors are analyzed and determined. Qualitative factors are applied in CBR to retrieve a similar case from the case bases for a new phone product and ANN is used to find the relationship between the quantitative factors and the predicted PUC. Finally, intensive experiments are conducted to test the effectiveness of six different forecasting models. The model proposed in this research is compared with the other five models and the MAPE value of the proposed model is the smallest. This research provides a new prediction model with high accuracy for mobile phone manufacturing companies.

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Financial distress prediction based on OR-CBR in the principle of k-nearest neighbors

Cited by 85 publications

References 40 publications

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

Hepatitis Disease Diagnosis Using Hybrid Case Based Reasoning and Particle Swarm Optimization

Forecasting of manufacturing cost in mobile phone products by case-based reasoning and artificial neural network models

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