Lectotype optimization of offshore platforms is of particular importance in the concept design process. Lectotype optimization involves multiple objectives with uncertainty and so is a problem of multiple attribute decision making. To date, there have been few published works on this topic in the context of offshore engineering. This paper develops a framework and methodology for evaluation of offshore platform alternatives, where a fuzzy optimum model is proposed to integrate the influence of each objective in the criteria set, and a new weight-assessing method is developed to mimic the decision maker’s experience and preference based on complementary pairwise comparisons. A case study shows that the new framework and methodology is scientific, reasonable and easy to use in practice.

Due to significance of the engineering system for flood control and the multi-dimensional synthesis of the risk evaluation issue that the paper selects typical risk indexes to classify risk degree of flood-control engineering. Under global view of system that the variable fuzzy sets method is presented to set up comprehensive evaluation model for flood-control engineering system (FCES). The method can scientifically and reasonably determine membership degrees and relative membership functions of disquisitive indexes at level interval that relating to engineering, also it can fully use one’s experience and knowledge, qualitative and quantitative information of index system to obtain weights of indexes for operating comprehensive risk evaluation for FCES. The numerical example shows that the proposed method is feasible and effective, and the evaluation results are reasonable.

This paper aims to develop a fuzzy dynamic programming approach for multiobjective multistage decision making problems. Fuzzy dynamic programming usually convert the problems into corresponding single objective problems by an aggregate of hybrid objective values that expresses the performance of the particular stage decision. Weightassessment is an important problem arising from the evaluation of multiple objectives. Therefore, a fuzzy iteration model is first developed to simultaneously provide the objective weights and the evaluation of alternatives with multiple objectives. Then a fuzzy dynamic programming is derived by applying the fuzzy iteration model to classic dynamic programming to evaluate the decisions at each stage in the dynamic process of decision makings, where the objective weights are initially elicited from the information implicit in alternatives and can be interactively adjusted to reflect the changes of decision situations by using a non-structured decision making analysis method if necessary. Finally, the fuzzy dynamic programming is validated through a problem of water resource allocation.

On the ground of fuzzy optimum selection of BP neural network model, the paper introduces genetic algorithm to the model and presents an intelligent decision-making model based on fuzzy optimum selection of BP neural network model and mixed with genetic algorithm. A case proved that the intelligent decision-making model is efficient and robust in determining network topologic structure, accelerating convergence velocity and enhancing the global optimum ability. The intelligent decision-making model is further development of the fuzzy optimum selection of BP neural network model.

黄河内蒙段地处黄河流域最北端,由于它的特殊地理位置、水文气象条件、河道特性,几乎每年产生凌汛。本文在分析影响凌汛成因因素的基础上,选取合适的预报因子,基于模糊优选神经网络BP模型, 提出冰凌预报方法, 应用于黄河内蒙段封河、开河日期的预报。结果表明, 计算简便, 精度良好。