A MULTIBLOCK PARTIAL LEAST SQUARES ALGORITHM FOR INVESTIGATING COMPLEX CHEMICAL SYSTEMS

The details of a general multiblock partial least squares(PLS)algorithm based on one originallypresented by Wold et al.have been developed and are completely presented.The algorithm can handlemost types of relationships between the blocks and constitutes a significant advancement in the modelingof complex chemical systems.The algorithm has been programmed in FORTRAN and has been testedon two simulated multiblock problems,a three-block and a five-block problem.The algorithm combinesthe score vectors for all blocks predicting a particular block into a new block.This new block is used topredict the predicted block in a manner analogous to the two-block PLS.In a similar manner if one blockpredicts more than one other block,the score vectors of all predicted blocks are combined to form a newblock,which is then predicted by the predictor block as in the two-block PLS.Blocks that both predictand are predicted are treated in such a way that both of these roles can be taken into account whencalculating interblock relationships.The results of numerical simulations indicate that the computerprogram is operating properly and that the multiblock PLS produces meaningful and consistent results.     

FUZZY MULTIVARIATE RULE-BUILDING EXPERT SYSTEMS:MINIMAL NEURAL NETWORKS

A fuzzy multivariate rule-building expert system (FuRES) has been devised which also functions as aminimal neural network.This system builds rules from training sets of data that use featuretransformation in their antecedents.The rules are constructed using the ID3 algorithm with a fuzzyexpression of classification entropy.The rules are optimal with respect to fuzziness and can accommodateoverlapped and underlapped clusters of data.The FuRES algorithm combines the benefits obtained fromsimulated annealing and gradient optimization,which provide robustness and efficiency respectively.FARES classification trees support OR logic in their inference.The system automatically generatesmeaningful and consistent certainty factors during rule construction.Unlike other neural networks,FuRES uses local processing which furnishes qualitative information in the rule structure of itsclassification trees and variable loadings of the weight vectors.     

海岸带的区域管理：发达资本主义国家的经验

当前对海岸带的科学兴趣和实践需要迅速增长,这一课题将成为现代区域科学(经济地理学、区域经济学、生态学、资源利用经济学等)的最具现实意义的课题之一。例如早在1973年联合国经济及社会理事会建议联合国秘书处采取相应措施来制定跨学科的海岸带发展和管理纲要。