State Transition Algorithm

In terms of the concepts of state and state transition, a new heuristic random search algorithm named state transition algorithm is proposed. For continuous function optimization problems, four special transformation operators called rotation, translation, expansion and axesion are designed. Adjusting measures of the transformations are mainly studied to keep the balance of exploration and exploitation. Convergence analysis is also discussed about the algorithm based on random search theory. In the meanwhile, to strengthen the search ability in high dimensional space, communication strategy is introduced into the basic algorithm and intermittent exchange is presented to prevent premature convergence. Finally, experiments are carried out for the algorithms. With 10 common benchmark unconstrained continuous functions used to test the performance, the results show that state transition algorithms are promising algorithms due to their good global search capability and convergence property when compared with some popular algorithms.Comment: 18 pages, 28 figure

A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

Multi-step ahead forecasting is still an open challenge in time series forecasting. Several approaches that deal with this complex problem have been proposed in the literature but an extensive comparison on a large number of tasks is still missing. This paper aims to fill this gap by reviewing existing strategies for multi-step ahead forecasting and comparing them in theoretical and practical terms. To attain such an objective, we performed a large scale comparison of these different strategies using a large experimental benchmark (namely the 111 series from the NN5 forecasting competition). In addition, we considered the effects of deseasonalization, input variable selection, and forecast combination on these strategies and on multi-step ahead forecasting at large. The following three findings appear to be consistently supported by the experimental results: Multiple-Output strategies are the best performing approaches, deseasonalization leads to uniformly improved forecast accuracy, and input selection is more effective when performed in conjunction with deseasonalization

Asthma in the elderly: what we know and what we have yet to know

In the past, asthma was considered mainly as a childhood disease. However, asthma is an important cause of morbidity and mortality in the elderly nowadays. In addition, the burden of asthma is more significant in the elderly than in their younger counterparts, particularly with regard to mortality, hospitalization, medical costs or health-related quality of life. Nevertheless, asthma in the elderly is still been underdiagnosed and undertreated. Therefore, it is an imperative task to recognize our current challenges and to set future directions. This project aims to review the current literature and identify unmet needs in the fields of research and practice for asthma in the elderly. This will enable us to find new research directions, propose new therapeutic strategies, and ultimately improve outcomes for elderly people with asthma. There are data to suggest that asthma in older adults is phenotypically different from young patients, with potential impact on the diagnosis, assessment and management in this population. The diagnosis of AIE in older populations relies on the same clinical findings and diagnostic tests used in younger populations, but the interpretation of the clinical data is more difficult. The challenge today is to encourage new research in AIE but to use the existing knowledge we have to make the diagnosis of AIE, educate the patient, develop a therapeutic approach to control the disease, and ultimately provide a better quality of life to our elderly patients

Moisture ratio prediction in drying process of agricultural products: A new correlation model

In this study, a new prediction model for fluidized bed drying is proposed. This correlation model has been developed by using Rayleigh dimensional analysis method. To obtain experimental results, a fluidized bed drying set-up was constructed and used in batch conditions. The prediction performance of the proposed model has been tested by using some agricultural products such as corn, bean, and chickpea. A good agreement is observed between the experimental and the model results. Correlation coefficient (R2) and root mean square error (RMSE) values were obtained as acceptable. In addition, another fluidized bed drying data were collected from the literature and used for showing the prediction performance of the model. Comparative evaluation results show that the proposed model can be used in prediction of moisture ratio (MR) for agricultural products. The absence of a general model for MR prediction in literature makes the proposed model valuable. © 2010 American Society of Agricultural and Biological Engineers