Reference health
Power prediction of waste heat recovery system for a cement plant using back propagation neural network and its thermodynamic modeling
24/24 checkable references clean · checked 2026-07-23
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
14 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 24 checked references that resolve
resolves10.1109/MEACS.2015.7414935
Energy prediction of a combined cycle power plant using a particle swarm optimization trained feedforward neural network
resolves10.1016/j.eswa.2005.06.009
Development of an artificial neural network-based software for prediction of power plant canal water discharge temperature
resolves10.1016/j.ijepes.2014.02.027
Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods
resolves10.1109/IS3C.2012.174
Modeling of Turbine Cycle Using Neuro-fuzzy Based Approach to Predict Turbine-Generator Output for Nuclear Power Plants
resolves10.1016/j.apenergy.2008.03.018
Development and multi-utility of an ANN model for an industrial gas turbine
resolves10.1016/j.egypro.2011.12.895
Using Recurrent Artificial Neural Networks to Forecast Household Electricity Consumption
resolves10.1016/j.ijepes.2016.03.012
Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm
resolves10.1109/ICRAS.2017.8071930
Corrosion detection in industrial pipes using guided acoustics and radial basis function neural network
resolves10.18178/ijoee.4.2.91-95
Prediction of Hourly Generated Electric Power Using Artificial Neural Network for Combined Cycle Power Plant
resolves10.1016/j.procs.2018.08.174
Prediction of heat energy from the naturally aspirated internal combustion engine exhaust gas using artificial neural network
resolves10.1016/j.applthermaleng.2018.05.039
Optimization of waste heat recovery power generation system for cement plant by combining pinch and exergy analysis methods
resolves10.1002/er.5956
Energy management strategy based on velocity prediction using back propagation neural network for a plug‐in fuel cell electric vehicle
resolves10.1504/IJEX.2013.054118
Application of artificial neural network to exergy performance analysis of coal fired thermal power plant
resolves10.1016/j.enconman.2020.113552
Performance prediction and optimization of an organic Rankine cycle (ORC) for waste heat recovery using back propagation neural network
resolves10.3390/pr8060661
A Feed-Forward Back Propagation Neural Network Approach to Predict the Life Condition of Crude Oil Pipeline
resolves10.1002/er.5979
Steam consumption prediction of a gas sweetening process with methyldiethanolamine solvent using machine learning approaches
resolves10.1002/er.5138
Performance assessment of steam Rankine cycle and sCO<sub>2</sub>Brayton cycle for waste heat recovery in a cement plant: A comparative study for supercritical fluids
resolves10.1016/j.enconman.2015.10.044
Energetic and exergetic analysis of a steam turbine power plant in an existing phosphoric acid factory
resolves10.1002/er.3166
Thermodynamic performance analysis of the coal-fired power plant with solar thermal utilizations
resolves10.1002/er.5130
Thermodynamic analysis of a novel fossil‐fuel–free energy storage system with a trans‐critical carbon dioxide cycle and heat pump
resolves10.1016/j.aei.2017.09.007
Wood defects classification using laws texture energy measures and supervised learning approach
The 14 references without a DOI — listed, not checked
no DOI — not checkedAll Pakistan Cement Manufacturer Association. July 2020. Available fromhttps://www.apcma.com/data_productioncapacity.html.
no DOI — not checkedWorld Cement. September 2020. Available from https://www.worldcement.com/europe‐cis/31072013/whr_cement_conventional_rankine_cycle_76/.
no DOI — not checkedKayaH TufekciP GurgenFS.Local and global learning methods for predicting power of a combined gas & steam turbine. International Conference on Emerging Trends in Computer and Electronics Engineering (ICETCEE); 2012.
no DOI — not checkedPerformance analysis of a combined cycle gas turbine under varying operating conditions
no DOI — not checkedSaiTK ReddyKA.Neural network applications in a power station; 2015.
no DOI — not checkedWankhedeA GhateV.Prediction of a combine cyle power plant using neural networks. 3rd IEEE International Conference on Recent Trends in Electronics Information & Communication Technology (RTEICT); 2018.
no DOI — not checkedLoad forecasting using back propagation algorithm
no DOI — not checkedTime series prediction using radial basis function neural network
no DOI — not checkedRainfall forecasting using backpropagation neural network
no DOI — not checkedEfficiency analysis of organic Rankine cycle with internal heat exchanger using neural network
no DOI — not checkedEnergy and exergy analysis of 210 MW Jamshoro thermal power plant
no DOI — not checkedEnergy and exergy analysis of steam and power generation plant
no DOI — not checkedLearn OpenCV. 2021. Available fromhttps://www.learnopencv.com/understanding‐feedforward‐neural‐networks/. Accessed January 1 2021.
no DOI — not checkedIntroduction to neural networks using Matlab 6.0
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