In recent times, the municipal solid waste generation is dramatically increasing due to factors such as rapid urbanization, altered living standard and increased population. These factors make the municipal solid waste management system complex and break the pollution controlling strategies. So that it necessitates the system to accurately predicts the waste composition. Based on waste classification, the suitable decomposition technique is preferred. Therefore, this paper proposed CMSOA

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... ed dual faster R-CNN based waste management system to accurately classify the waste composition. The proposed system is formed by hybridizing dual faster RCNN along with Complex-Valued Encoding Multi-chain Seeker Optimization Algorithm (CMSOA). Various evaluation measures namely accuracy, precision, recall, F-measure, RMSE, MAE, MAPE metrics are computed and the case study analysis is conducted on major five cities of Maharashtra. The comparative analysis is carried out for various approaches and from the analysis the results revealed that the proposed method provides better classification results than other methods