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Application and integration of multiple linear regression and linear programming in renewable resource analyses



Application and integration of multiple linear regression and linear programming in renewable resource analyses



J Range Manage 19(6): 356-362



As more is learned about range complexes and the interrelationships of their components better mathematical expression of these factors will be possible. Mathematical expression of environmental relationships is necessary if there is to be utilization of many of the powerful new tools that were developed in operations research and systems analysis for study of complex systems. An example of this approach was given. Multiple linear regression equations were developed to interrelate 5 dependent vegetation yield and composition variables, each with 11 independent soil and topographic variables. These multiple regression equations were used as the objective and function and as constraints in a linear programming model to determine the values for site factors for the maximum crude protein yield from a foothill range. Suggestions also were made concerning the applicability of some mathematical programming techniques in resource management analysis.

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