scholarly journals Development and Evaluation of Combined Adaptive Neuro-Fuzzy Inference System and Multi-Objective Genetic Algorithm in Energy, Economic and Environmental Life Cycle Assessments of Oilseed Production

2020 ◽  
Vol 13 (1) ◽  
pp. 290
Author(s):  
Seyed Hashem Mousavi-Avval ◽  
Shahin Rafiee ◽  
Ali Mohammadi
Keyword(s):  
Genetic Algorithm ◽  
Life Cycle ◽  
Fuzzy Inference ◽  
Cost Ratio ◽  
Inference System ◽  
Benefit Cost Ratio ◽  
Multi Objective Genetic Algorithm ◽  
Neuro Fuzzy ◽  
Environmental Emissions ◽  
Benefit Cost

Energy consumption, economics, and environmental impacts of canola production were assessed using a combined technique involving an adaptive neuro-fuzzy inference system (ANFIS) and a multi-objective genetic algorithm (MOGA). Data were collected from canola farming enterprises in the Mazandaran province of Iran and were used to test the application of the combined modeling algorithms. Life cycle assessment (LCA) for one ha functional unit of canola production from cradle to farm gate was conducted in order to evaluate the impacts of energy, materials used, and their environmental emissions. MOGA was applied to maximize the output energy and benefit-cost ratio, and to minimize environmental emissions. The combined ANFIS–MOGA technique resulted in a 6.2% increase in energy output, a 144% rise in the benefit-cost ratio, and a 19.8% reduction in environmental emissions from the current canola production system in the studied region. A comparison of ANFIS–MOGA with the data envelopment analysis approach was also conducted and the results established that the former is a better system than the latter because of its ability to generate optimum conditions that allow for the assessment of a combination of parameters such as energy, economic, and environmental impacts of agricultural production systems.

scholarly journals Optimization of EPB Shield Performance with Adaptive Neuro-Fuzzy Inference System and Genetic Algorithm

2019 ◽  
Vol 9 (4) ◽  
pp. 780 ◽  
Author(s):  
Khalid Elbaz ◽  
Shui-Long Shen ◽  
Annan Zhou ◽  
Da-Jun Yuan ◽  
Ye-Shuang Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Pressure Balance ◽  
Anfis Model ◽  
Inference System ◽  
Advance Rate ◽  
Multi Objective ◽  
Neuro Fuzzy ◽  
Epb Shield

The prediction of earth pressure balance (EPB) shield performance is an essential part of project scheduling and cost estimation of tunneling projects. This paper establishes an efficient multi-objective optimization model to predict the shield performance during the tunneling process. This model integrates the adaptive neuro-fuzzy inference system (ANFIS) with the genetic algorithm (GA). The hybrid model uses shield operational parameters as inputs and computes the advance rate as output. GA enhances the accuracy of ANFIS for runtime parameters tuning by multi-objective fitness function. Prior to modeling, datasets were established, and critical operating parameters were identified through principal component analysis. Then, the tunneling case for Guangzhou metro line number 9 was adopted to verify the applicability of the proposed model. Results were then compared with those of the ANFIS model. The comparison showed that the multi-objective ANFIS-GA model is more successful than the ANFIS model in predicting the advance rate with a high accuracy, which can be used to guide the tunnel performance in the field.

Modeling of rheological behavior of honey using genetic algorithm–artificial neural network and adaptive neuro-fuzzy inference system

2015 ◽  
Vol 9 ◽  
pp. 60-67 ◽  
Author(s):  
Marziyeh Ramzi ◽  
Mahdi Kashaninejad ◽  
Fakhreddin Salehi ◽  
Ali Reza Sadeghi Mahoonak ◽  
Seyed Mohammad Ali Razavi
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Rheological Behavior ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Artificial Neural

scholarly journals Analysis of alternative selection for vertical clearance design under Tabalong Bridge of PT Adaro Indonesia

2022 ◽  
Vol 4 (1) ◽  
pp. 7-30
Author(s):  
Diean Oktavian Regar ◽  
Aqli Mursadin
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Secondary Data ◽  
Primary Data ◽  
Cost Ratio ◽  
Benefit Cost Ratio ◽  
Bcr Method ◽  
Benefit Cost ◽  
National Road ◽  
Alternative Designs

PT Adaro Indonesia is trying to adjust a vertical clearance under Tabalong Bridge 1 (unloaded) and Tabalong Bridge 2 (loaded) because the existing conditions still apply a minimum vertical clearance of 4 m. I t should be in accordance with latest Regulation of the Minister of Public Works No. 19/PRT/M/2011 that for vertical clearance above national road at least 5.1 m. This specification has not been met by the national road under the Tabalong 1 & 2 Bridges bec ause both bridges were built in the 90s. Therefore we need an engineering technique to overcome this. There are 2 alternative designs, namely lowering the elevation of the national road and increasing the elevation of the bridge's upper structure to mitiga te oversized vehicles so as not to hit the lower structure of the Tabalong bridge. In determining the selection of the best alternative designs in this research is based on two (2) things, non financial criteria with Analytical Hierarchy Process (AHP) and financial criteria with Life Cycle Cost Analysis (LCCA)/Benefit Cost Ratio (BCR) method. This study uses a survey method by distributing questionnaires and interviews as a means of collecting primary data. In addition, previous research and consultant DED documents were used as a means of collecting secondary data. The AHP method is used to process primary data to produce a decision from a non financial aspect. While the LCC/BCR method is used to process secondary data to produce a decision from the financi al aspect . The results of the AHP analysis obtained that the synthesis value of the decision the option of lowering national roads was 85% and the bridge lifting option was 15% and the consistency ratio (CR) was 0.05 < 0.1. The consistency ratio below 0.1 shows that the questionnaire data from the respondents are consistent. The results of the analysis of Life Cycle Cost (LCC) obtained the option of lowering national roads where the LCC value is Rp. 44,877,651,669.27 more economical than the bridge lifting option. Then the results of the Benefit Cost Ratio (BCR) analysis obtained the option of lowering national roads with a BCR value of 2.33 > 1 and NPV = Rp. 43,442,264,804.34 > 1 means that the option lowering national roads is feasible. While the bridge li fting option is obtained by analyzing the value of BCR = 0.98 < 1 and NPV = option is not feasible to implement.

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