Fuzzy Rule-based System for Corruption Control in Nigerian Police Force

This paper has attempted to develop an artificial intelligence model based on fuzzy logic for the control of corruption in Nigerian Police Force. The researcher employed fuzzy rule-base inference system methodology using four inputs variables; funding, logistics and operational equipment (FLOE) condition of service, remuneration and motivation (CSRM), recruitment, training and promotion (RTP), confidence and support by the community (CSC) were used to determine the corruption severity level. An output variable; corruption severity level (CSL) was adopted for the model development. The simulation was carried out using MATLAB 2015 for Windows. The results revealed that it is very obvious for Nigeria as a country to have a Police Force whose corruption severity level is low. Thus (i) Condition of service, remunerations and motivation has to be excellent; (ii) Funding, logistics and operational equipment has to be adequate; (iii) Recruitment, training and promotion has to be excellent, and finally (iv) Confidence and support by the community has to be very high.