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721.
Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R2 were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R2 confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.  相似文献   
722.
Environmental Science and Pollution Research - The increasing intensification of the aquaculture industry requires the development of new strategies to reduce the negative impacts of wastewater on...  相似文献   
723.
724.

The present study investigates the feasibility of using two types of municipality solid wastes incineration ashes, namely, fly ash and bottom ash in the production of sustainable alkali-activated binder. The ashes are collected from the incineration plant and characterized to determine their particle size distribution, specific gravity, chemical composition, and heavy metals content. The ashes are then used as either fly ash or sand replacement with five replacement ratios 0%, 5%, 10%, 15%, and 20% to produce the binder. The produced binder are characterized in terms of strength, workability, density, water absorption, thermal conductivity and stability, chemical composition, and heavy metals content. The results reflect the ability of producing sustainable alkali-activated binder with small dosage of MSWI ashes as either fly ash or sand replacement without negatively affecting its strength, workability, density, and water absorption. The ashes enhance the thermal insulation capability of the binder.

  相似文献   
725.
Environmental Science and Pollution Research - Anthropogenic and natural factors lead to substantial environmental degradation. This shift is aligned with the country's overall development,...  相似文献   
726.
Environmental Science and Pollution Research - This study analyzes the effects of credit constraints on technical efficiency of Boro rice growers in the district of Pabna in Bangladesh. Using a...  相似文献   
727.
Environmental Science and Pollution Research - In recent years, green roofs have become the subject of increasing interest because of their good aesthetic qualities, energy conservation, and...  相似文献   
728.
Environmental Science and Pollution Research - This study of a downstream segment (Brahmaputra, Bangladesh) of one of the longest transboundary (China-India-Bangladesh) Himalayan rivers reveals...  相似文献   
729.
Journal of Polymers and the Environment - The present study aimed to evaluate the characteristics of alginate beads filled with thyme and clove essential oils nanoemulsions (EONs). The droplet size...  相似文献   
730.
Environmental Science and Pollution Research - As the world continues to cope with the COVID-19 pandemic, emerging evidence indicates that respiratory transmission may not the only pathway in which...  相似文献   
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