en Artificial Intelligence Techniques Artificial Intelligence Techniques Research Paper Research Paper <span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times=""><span style="color:black">This paper proposes a novel approach to analyzing and managing electricity consumption using a clustering algorithm and a high-accuracy classifier for smart meter data. The proposed method utilizes a multilayer perceptron neural network classifier optimized by an Imperialist Competitive Algorithm (ICA) called ICA-optimized MLP, and a CD Index based on Fuzzy c-means to optimally determine representative load curves. A case study involving a real dataset of residential smart meters is conducted to validate the effectiveness of the proposed method, and the results demonstrate that the ICA-optimized MLP method achieves an accuracy of 98.62%, outperforming other classification methods. This approach has the potential to improve energy efficiency and reduce costs in the power system, making it a promising solution for analyzing and managing electricity consumption</span></span></span><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times="">.</span></span> Smart Meter, Fuzzy C-Means, MLP Neural Network, ICA Algorithm, Residential Electricity Customers. 101 116 http://ijeee.iust.ac.ir/browse.php?a_code=A-10-1854-3&slc_lang=en&sid=1 Pardis Asghari pardisasghari43@gmail.com 1800319475328460013237 1800319475328460013237 No University of Science and Technology of Mazandaran Alireza Zakariazadeh zakaria@mazust.ac.ir 1800319475328460013238 0000000164000999 Yes University of Science and Technology of Mazandaran