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A new Adaptive Neuro Particle Swarm Optimization (ANPSO) combined with afuzzy inference system for diagnosing disorders is presented in this paper. Themain contributions of the novel proposed method can be a global search acrossthe whole search space with faster convergence rate. Moreover, it shows abetter exploration and exploitation by applying the adaptive controlparameters, automatic control of inertia weight and coefficient of personal andsocial behaviours. Utilizing such attributes lead to a fast and smart diagnosismechanism which is able to diagnosis the diseases by the high accuracy. TheANPSO is associated with tuning the characteristics of the inference system toachieve the minimum diagnosis error as far as the optimized model is obtained.As a case study, we use liver disorders dataset called Bupa. According to thepreliminary ramifications, the suggested adaptive PSO performance can overcomethe traditional inference system and combined with other optimization methodssubstantially.

Adaptive Neuro Particle Swarm Optimization applied for diagnosing disorders