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Keywords: Support vector regression (SVR) Hybrid genetic algorithm (HGA) Parameter optimization Kernel function optimization Electrical load forecasting Forecasting accuracy a b s t r a c t This study developed a novel model, HGA-SVR, for type of kernel function and kernel parameter value optimization in support vector regression (SVR), which is then(More)
OBJECTIVES Liver disease, the most common disease in Taiwan, is not easily discovered in its initial stage; early diagnosis of this leading cause of mortality is therefore highly important. The design of an effective diagnosis model is therefore an important issue in liver disease treatment. This study accordingly employs classification and regression tree(More)
The symptoms of liver diseases are not apparent in the initial stage, and the condition is usually quite serious when the symptoms are obvious enough. Most studies on liver disease diagnosis focus mainly on identifying the presence of liver disease in a patient. Not many diagnosis models have been developed to move beyond the detection of liver disease. The(More)
As changes in the medical environment and policies on national health insurance coverage have triggered tremendous impacts on the business performance and financial management of medical institutions, effective management becomes increasingly crucial for hospitals to enhance competitiveness and to strive for sustainable development. The study accordingly(More)
The prediction of business failure is an important and challenging issue that has served as the impetus for many academic studies over the past three decades. The widely applied methods to predict the risk of business failure were the classic statistical methods, data mining and machine learning techniques. Case Based-Reasoning (CBR) is an inductive machine(More)