This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components ...

Through a series of studies, involving over 400 companies over 20 years, the University of Tennessee Sales Forecasting Research Team has developed a vision of world-class forecasting. This presentation will articulate that vision, and participants will leave with a framework for benchmarking their own forecasting processes. Specifically, attendees will learn: • What forecasting excellence consi...

three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted msfe method. these methods assign the different weights that can not change at each time point to each individual forecasting model. in this study, we introduce the iowga operator combination method which can overcome the defect of previous three combin...

An organization needs to develop a forecasting system involving several approaches to predicting uncertain events. Such forecasting systems require the development of expertise in identifying forecasting problems, applying a range of forecasting methods, selecting appropriate methods for each problem, and evaluating and refining forecasting methods over time. It is also important to have strong...

Nitrification was studied with microsensors and fluorescence in situ hybridization (FISH) in sandy sediment of a small lowland stream. Comparative measurements were performed in both intact field sediment (‘natural sediment’) and sediment from the same site after processing for a laboratory incubation experiment (‘manipulated sediment’). In natural sediment, the nitrification activity and abund...

A quasi-three-dimensional suspended sediment transport model was developed and generalized to include combined wave-current effects to study bottom sediment resuspension and transport in southern Lake Michigan. The results from a threedimensional circulation model and a wind wave model were used as input to the sediment transport model. Two effects of nonlinear wave-current interactions were co...

During waning flood flows in gravel-bed streams, finegrained bedload sediment (sand and fine gravel) is commonly winnowed from zones of high shear stress, such as riffles, and deposited in pools, where it mantles an underlying coarse layer. As sediment load increases, more fine sediment becomes available to fill pools. The volume of fine sediment in pools can be measured by probing with a metal...

Heavily polluted sediment is becoming an important part of water pollution, and this situation is particularly acute in developing countries. Sediment has gradually changed from being the pollution adsorbent to the release source and has influenced the water environment and public health. In this study, we evaluated the pollutant distribution in sediment in a heavily polluted river and agitated...

In this paper, we presented the performance of forecasting model and error correction will affect the accuracy of short-term load forecasting. Least squares support vector machines (LS-SVM) based on improved particle swarm optimization is selected as load forecasting model. Forecasting accuracy and generalization performance of LS-SVM depend on selection of its parameters greatly. Adaptive part...