This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation.In case-based reasoning systems,case representation is critical,and thus,researc...This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation.In case-based reasoning systems,case representation is critical,and thus,researchers have thoroughly investigated textual,attribute-value pair,and ontological representations.As big databases result in slow case retrieval,this research suggests a fast case retrieval strategy based on an associated representation,so that,cases are interrelated in both either similar or dissimilar cases.As soon as a new case is recorded,it is compared to prior data to find a relative match.The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches.Hierarchical Long Short-Term Memory(HLSTM)is used to evaluate the efficiency,similarity of the models,and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year.Based on the results,the proposed approaches allows for rapid case retrieval with high accuracy.展开更多
基金The authors would like to express their gratitude to the ministry of education and the deanship of scientific research-Najran University-Kingdom of Saudi Arabia for their Financial and Technical support under code number(code NU/-/SERC/10/643).
文摘This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation.In case-based reasoning systems,case representation is critical,and thus,researchers have thoroughly investigated textual,attribute-value pair,and ontological representations.As big databases result in slow case retrieval,this research suggests a fast case retrieval strategy based on an associated representation,so that,cases are interrelated in both either similar or dissimilar cases.As soon as a new case is recorded,it is compared to prior data to find a relative match.The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches.Hierarchical Long Short-Term Memory(HLSTM)is used to evaluate the efficiency,similarity of the models,and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year.Based on the results,the proposed approaches allows for rapid case retrieval with high accuracy.
