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Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM)

Research article (Arabian Journal for Science and Engineering, 2021) · cited 33× · AI/ML
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Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM)

Summary

Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM) is a scholarly article[1].

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  • Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM)'s instance of is recorded as scholarly article[2].

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Direct Wikidata claims

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM). Retrieved May 24, 2026, from https://4ort.xyz/entity/prediction-of-dry-sliding-wear-response-of-almg1sicu-silicon-carbide-molybdenum-disulphide-hybrid-composites-using-adapt
MLA “Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM).” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/prediction-of-dry-sliding-wear-response-of-almg1sicu-silicon-carbide-molybdenum-disulphide-hybrid-composites-using-adapt.
BibTeX @misc{4ortxyz_prediction-of-dry-sliding-wear-response-of-almg1sicu-silicon-carbide-molybdenum-disulphide-hybrid-composites-using-adapt_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM)}}, year = {2026}, url = {https://4ort.xyz/entity/prediction-of-dry-sliding-wear-response-of-almg1sicu-silicon-carbide-molybdenum-disulphide-hybrid-composites-using-adapt}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Prediction of Dry Sliding Wear Response of AlMg1SiCu/Silicon Carbide/Molybdenum Disulphide Hybrid Composites Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Response Surface Methodology (RSM) — https://4ort.xyz/entity/prediction-of-dry-sliding-wear-response-of-almg1sicu-silicon-carbide-molybdenum-disulphide-hybrid-composites-using-adapt (retrieved 2026-05-24)

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