Zobrazeno 1 - 10
of 25 664
pro vyhledávání: '"adaptive neuro-fuzzy inference"'
Publikováno v:
Energy Storage and Saving, Vol 3, Iss 4, Pp 259-269 (2024)
In response to the growing demand for electricity and the depletion of fossil fuel resources, nations are transitioning towards renewable energy systems as viable alternatives for power generation. Wind and solar photovoltaic (SPV) energy systems hav
Externí odkaz:
https://doaj.org/article/b126c3968c2747839f6c072cf370e654
Autor:
Shaymaa Alsamia, Edina Koch
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract This paper introduces a novel approach using Clustered Artificial Neural Networks (CLANN) to address the challenge of developing predictive models for multimodal dataset with extreme parameter values. The CLANN method strategically decompose
Externí odkaz:
https://doaj.org/article/8b9168b18ce44d0c969a8ee20022dbcb
Autor:
A. Saravanan, S. Rama Sree, M. Sreenivasa Reddy, Elumalai PV, Krishnasamy Karthik, Ashok Kumar Cheeli, Nasim Hasan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Four distinct neural models were used to evaluate the efficiency of a V-trough solar water heater (VTSWH) equipped with square-cut twisted tape (SCTT) and V-cut twisted tape (VCTT) at two different twist ratios, 3 and 5. The objective of thi
Externí odkaz:
https://doaj.org/article/9ccd81e8e11f4735bf5f8d391ec8ca5f
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract Fuel cells are the most promising energy source for the future energy demand. The automobile industry is looking at the integration of fuel cells with electric vehicles (EV). This integration comes with many challenges like dynamic operation
Externí odkaz:
https://doaj.org/article/21597785e7254d7dba0452b513b2abed
Autor:
George Uwadiegwu Alaneme, Kolawole Adisa Olonade, Ebenezer Esenogho, Mustapha Muhammad Lawan, Edward Dintwa
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-39 (2024)
Abstract This research explores the application of Artificial Intelligence (AI) techniques to assess the mechanical properties of geopolymer concrete made from a blend of Banana Peel-Ash (BPA) and Sugarcane Bagasse Ash (SCBA), using a sodium silicate
Externí odkaz:
https://doaj.org/article/4c25ddcaf77b4d53aa0d9bcac9635c8d
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-16 (2024)
Abstract This article presents an investment recommender system based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) and pre-trained weights from a Multimodal Neural Network (MNN). The model is designed to support the investment process for the
Externí odkaz:
https://doaj.org/article/7bc2a1cb480148a7a6dfbaf63582ee2e
Publikováno v:
Blockchain: Research and Applications, Vol 5, Iss 4, Pp 100231- (2024)
Due to recent fluctuations in cryptocurrency prices, Ethereum has gained recognition as an investment asset. Given its volatile nature, there is a significant demand for accurate predictions to guide investment choices. This paper examines the most i
Externí odkaz:
https://doaj.org/article/5eac1f2cce774bc7b3548539d3b9b172
Autor:
Pouya Mottahedin, Benyamin Chahkandi, Reza Moezzi, Amir M. Fathollahi-Fard, Mojtaba Ghandali, Mohammad Gheibi
Publikováno v:
Heliyon, Vol 10, Iss 21, Pp e39783- (2024)
Accurately predicting air quality concentrations is a challenging task due to the complex interactions of pollutants and their reliance on nonlinear processes. This study introduces an innovative approach in environmental engineering, employing artif
Externí odkaz:
https://doaj.org/article/138509f03343424ab84c943f17e120c2
Autor:
Abderrahmane Moussaoui, Djilani Ben Attous, Habib Benbouhenni, Youcef Bekakra, Benharir Nedjadi, Z.M.S. Elbarbary
Publikováno v:
Heliyon, Vol 10, Iss 21, Pp e39738- (2024)
This paper presents an adaptive neuro-fuzzy inference system (ANFIS) based on 24 sectors direct torque command (DTC) for a doubly-fed induction machine (DFIM) by using a 3-level neutral point clamped inverter. The DTC approach is used in this paper w
Externí odkaz:
https://doaj.org/article/8d2da0ddfff64c52be409df2eaccb4da
Publikováno v:
Petroleum Research, Vol 9, Iss 2, Pp 176-192 (2024)
In the petroleum industry, the analysis of petrophysical parameters is critical for efficient reservoir management, production optimization, development strategies, and accurate hydrocarbon reserve estimations. Over recent years, the integration of m
Externí odkaz:
https://doaj.org/article/f74f7d6f1cd14318ba1a60b4b51950f3