This study developed a classification model for monitoring the risk of sexually transmitted diseases (STDs) among females using information about non-invasive risk factors. Structured interview with physicians was done in order to identify the risk factors that are associated with the risk of STDs in Nigeria. The model was simulated using the fuzzy logic toolbox accessible in the MATLAB® R2015a Software. The results showed that nine non-invasive risk factors were associated with the risk of STDs among female patients in Nigeria. Two, three, and four triangular membership functions were appropriate for the formulation of the linguistic variables of the factors while the target risk was formulated using four triangular membership functions for the linguistic variables namely no risk, low risk, moderate risk, and high risk. The study concluded that the fuzzy logic model approach was adequate for predicting the risk of STDs based on the knowledge of the risk factors.

This study aims to formulate a classification model which farmers can use to determine the suitability of a land for supporting cultivation based on information about identified factors. Structured interview with farmers and agro-specialists were conducted in order to identify the factors associated with the classification of land suitability. Fuzzy membership function was used to formulate the input and output variables of the classification model for land suitability based on the risk factors identified. The model was simulated using MATLAB® R2015b -Fuzzy Logic Tool. The results showed that 7 risk factors were associated with the classification of the suitability of land for crop planting. The risk factors identified are annual rainfall, months of dry season, relative humidity, abundance of clay soil, abundance of sand soil, abundance of organic carbon and pH value of soil on land. 2 and 3 triangular membership functions were appropriate for the formulation of the linguistic variables of the factors using appropriate linguistic variables while the target suitability of land was formulated using four triangular membership functions for the linguistic variables unsuitable, fairly suitable, moderately suitable and highly suitable. 288 inferred rules were formulated using IF-THEN statements which adopted the values of the factors as antecedent and the suitability of land for planting crops as the consequent part of each rule. This study concluded that based on the assessment of information about the factors associated with the classification of land suitability a reasonable conclusion can be made about the possible use of land.