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Modeling a High Concentrator Photovoltaic Module Using Fuzzy Rule-Based Systems

Manuel Angel Gadeo-Martos, Antonio Jesús Yuste-Delgado, Florencia Almonacid Cruz, Jose-Angel Fernandez-Prieto et al. • Energies (2019)

Currently, there is growing interest in the modeling of high concentrator photovoltaic modules, due to the importance of achieving an accurate model, to improve the knowledge and understanding of this technology and to promote its expansion...

DOAJ Open Access (DOAJ) DOI: 10.3390/en12030567

Artificial neural network modeling of mixed convection viscoelastic hybrid nanofluid across a circular cylinder with radiation effect: Case study

Syed M. Hussain, Rahimah Mahat, Nek Muhammad Katbar, Imran Ullah et al. • Case Studies in Thermal Engineering (2023)

As a result of its use in the manufacturing and construction industries, research on the flow of nanofluid is rather well-known among academics and professionals in related fields. It is helpful for electrical equipment to utilize it for co...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.csite.2023.103487

Prognostic techniques for aeroengine health assessment and Remaining Useful Life estimation

Caricato A., Ficarella A., Chiodo L. Spada • E3S Web of Conferences (2021)

Predictive maintenance is the latest frontier in the management and maintenance of many industrial assets, including aeroengines. Made possible by last decades advances in monitoring equipment and machine learning algorithms, it permits ind...

DOAJ Open Access (DOAJ) DOI: 10.1051/e3sconf/202131211017

Explainable machine learning in materials science

Xiaoting Zhong, Brian J. Gallagher, Shusen Liu, Bhavya Kailkhura et al. • npj Computational Materials (2022)

Abstract Machine learning models are increasingly used in materials studies because of their exceptional accuracy. However, the most accurate machine learning models are usually difficult to explain. Remedies to this problem lie in explaina...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41524-022-00884-7

Testing the Physical Parameter Constraining Power of HCN and HNC with Neural Networks

Erica Behrens, Jeffrey G. Mangum, Mathilde Bouvier, Cosima Eibensteiner et al. • The Astrophysical Journal (2026)

We quantify the utility of HCN and HNC to characterize gas conditions in the nearby starburst galaxy NGC 253. We use measurements from the Atacama Large Millimeter/Submillimeter Array (ALMA) Large Program ALCHEMI: the ALMA Comprehensive Hig...

DOAJ Open Access (DOAJ) DOI: 10.3847/1538-4357/ae3567

Numerical investigation of corroded middle‐high strength pipeline subjected to combined internal pressure and axial compressive loading

Linlin Lu, Lecai Liang • Energy Science & Engineering (2021)

Abstract Buried oil and gas pipelines may face the threat of geological disasters such as landslides, faults, and floods. However, long‐term buried oil and gas pipelines often have corrosion defects, which bring greater challenges to the sa...

DOAJ Open Access (DOAJ) DOI: 10.1002/ese3.830

Machine Learning–Based Prediction of Organic Solar Cell Performance Using Molecular Descriptors

Mohammed Saleh Alshaikh • International Journal of Emerging Research in Engineering, Science, and Management (2025)

The performance of Organic Solar Cells (OSCs) is intrinsically linked to the molecular, electronic, and structural properties of donor and acceptor materials. This study employs various machine learning techniques, namely the Generalized Re...

DOAJ Open Access (DOAJ) DOI: 10.58482/ijeresm.v4i4.4

Quantum Computing in Transportation Engineering: A Survey

Shriyank Somvanshi, Md Monzurul Islam, Sazzad Bin Bashar Polock, Gaurab Chhetri et al. • IEEE Transactions on Intelligent Transportation Systems (2026)

Quantum computing introduces new computational methods that address complex optimization and machine learning challenges in transportation engineering. This literature survey reviews fundamental quantum principles, including qubits, superpo...

OPENALEX Open Access DOI: https://doi.org/10.1109/tits.2026.3662626

Computing with Bees: Attacking Complex Transportation Engineering Problems

Panta Lučić, Dušan Teodorović • International Journal of Artificial Intelligence Tools (2003)

The Bee System (an artificial bee swarm) is introduced in this paper. The proposed approach is applied to the Traveling Salesman Problem. The obtained results are very promising. The potential applications of the developed Bee System in the...

OPENALEX DOI: https://doi.org/10.1142/s0218213003001289

Encyclopedic Dictionary of Applied Geophysics

Robert E. Sheriff • Society of Exploration Geophysicists eBooks (2002)

The fourth edition of SEG's best seller is a valuable, comprehensive reference that is a must for every geophysicist, geologist, explorationist, engineer, energy adviser, economist, editor, and student involved in the field. Hundreds of ter...

OPENALEX DOI: https://doi.org/10.1190/1.9781560802969

A geotechnical investigation on a recent gigantic rock avalanche at the Patalganga-Langsi site on the Badrinath highway of chamoli, Uttarakhand (Garhwal Himalaya), India

Biswajit Bera • Discover Geoscience (2025)

Abstract Garhwal Himalaya is one of the most landslide-prone regions in the Himalayan Belt due to its seismo-tectonic background, geological complexity, climate, geomorphological setting and large-scale human interference. A gigantic rock a...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44288-025-00238-y

Generating Daily High-Resolution Regional XCO<sub>2</sub> by Deep Neural Network and Multi-Source Data

Wenjie Tian, Lili Zhang, Tao Yu, Dong Yao et al. • Atmosphere (2024)

CO2 is one of the primary greenhouse gases impacting global climate change, making it crucial to understand the spatiotemporal variations of CO2. Currently, commonly used satellites serve as the primary means of CO2 observation, but they of...

DOAJ Open Access (DOAJ) DOI: 10.3390/atmos15080985

An artificial neural network-based model for predicting paratransit travel time

George Ukam, Charles Adams, Atinuke Adebanji, Williams Ackaah • Cogent Engineering (2024)

The nature of paratransit services makes for increased uncertainty in trip time, leading to reported unreliability and dissatisfaction by the users. While providing travel information has proved helpful in formal bus services and has been r...

DOAJ Open Access (DOAJ) DOI: 10.1080/23311916.2024.2386383

Optimizing runoff prediction in plains river network areas: a hybrid XAJ-BP modelling framework with basin structure division

Xu Cheng, Shiqiang Wu, Jiangyu Dai, Xiufeng Wu et al. • Engineering Applications of Computational Fluid Mechanics (2026)

The plain water network area is characterized by its flat terrain and a dense crisscrossing of rivers. The runoff process in this region is significantly influenced by human activities, resulting in a complex relationship between water stor...

DOAJ Open Access (DOAJ) DOI: 10.1080/19942060.2026.2749141

Information models for machine vision systems

A. L. Okhotnikov • Интеллектуальный транспорт (2026)

The article examines the information models used in machine vision systems. The content of machine vision systems is disclosed in terms of their belonging to the field of information technology. Two main subsystems are described. The main i...

DOAJ Open Access (DOAJ)

Application of the convolutional neural network in partial discharge spectrum recognition of power apparatus

Feng‐Chang Gu • IET Science, Measurement & Technology (2023)

Abstract Partial discharge (PD) detection is used to evaluate the insulation status of high‐voltage equipment. The most challenging aspect of traditional PD recognition is extracting features from the discharge signal. Accordingly, this stu...

DOAJ Open Access (DOAJ) DOI: 10.1049/smt2.12137