鱼群洄游预测与生态经济问题研究

鱼群洄游预测研究对于渔业资源的可持续开发和利用是十分重要的。文章建立了基于RBF神经网络的鱼群洄游预测模型。研究结果表明,所提出的神经网络模型对于改进鱼群洄游的预测精度十分有效。渔业资源的可持续发展需要广泛、多领域的相互协作,并且需要自然科学与社会科学以及管理策略的相互结合。渔业生态经济的核心问题是处理好渔业经济发展与渔业生态保护的问题。

Forecasting Fish Stock Recruitment and Its Effect to Ecological Economy

The estimation and forecasting of recruitment has been a persistent preoccupation of fisheries scientists because of the critical importance of recruitment to the exploitable segment of the stock.RBF neural network model is developed to forecast the recruiting biomass of fish.The investigations demonstrate how neural network can be used to improve the accuracy of fishery stock forecasts.Sustainable governance of the fisheries resources requires a broad,transdisciplinary perspective that can integrate across the natural and social sciences and the policy process.The core problem addressed in fishery ecological economics is the sustainability of interactions between economic and ecological systems.