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ssrn.4905242

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/er.6584openalex-extracted

Research on optimum tilt angle of photovoltaic module based on regional clustering of influencing factors of power generation

inferredcites →https://doi.org/10.1016/j.apenergy.2021.117017openalex-extracted

An optimization approach to photovoltaic building integration towards low energy buildings in different climate zones

inferredcites →https://doi.org/10.1016/j.enconman.2022.115563openalex-extracted

Computationally expedient Photovoltaic power Forecasting: A LSTM ensemble method augmented with adaptive weighting and data segmentation technique

inferredcites →https://doi.org/10.1016/j.renene.2016.08.037openalex-extracted

Influences of environmental factors on Si-based photovoltaic modules after longtime outdoor exposure by multiple regression analysis

inferredcites →https://doi.org/10.1016/j.rser.2020.110339openalex-extracted

Photovoltaic module regional clustering in mainland China and application based on factors influencing field reliability

inferredcites →https://doi.org/10.1016/j.rser.2022.112950openalex-extracted

Building PV integration according to regional climate conditions: BIPV regional adaptability extending Köppen-Geiger climate classification against urban and climate-related temperature increases

inferredcites →https://doi.org/10.1016/j.seta.2021.101526openalex-extracted

Comparative investigation of performance evaluation, degradation causes, impact and corrective measures for ground mount and rooftop solar PV plants – A review

inferredcites →https://doi.org/10.1016/j.seta.2022.102620openalex-extracted

A method for determining the applicable geographical regions of PV modules field reliability assessment results based on regional clustering of environmental factors and their weights

inferredcites →https://doi.org/10.1016/j.solener.2017.01.046openalex-extracted

A novel climate classification criterion based on the performance of solar photovoltaic technologies

inferredcites →https://doi.org/10.1016/j.solener.2019.08.072openalex-extracted

Methodology of Köppen-Geiger-Photovoltaic climate classification and implications to worldwide mapping of PV system performance

inferredcites →https://doi.org/10.1038/s41597-020-0453-3openalex-extracted

Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

inferredcites →https://doi.org/10.1080/19942060.2022.2126528openalex-extracted

Investigating photovoltaic solar power output forecasting using machine learning algorithms

inferredcites →https://doi.org/10.1109/pvsc.2016.7749919openalex-extracted

Determining the effects of environment and atmospheric parameters on PV field performance

inferredcites →https://doi.org/10.1109/pvsc40753.2019.8980831openalex-extracted

Photovoltaic Degradation Climate Zones

inferredcites →https://doi.org/10.13140/rg.2.2.17025.76648openalex-extracted

A simple algorithm for the computation of the spectral distribution of the solar irradiance at surface

inferredcites →https://doi.org/10.3390/app11167550openalex-extracted

A State-of-Art-Review on Machine-Learning Based Methods for PV

inferredcites →https://doi.org/10.3390/en12142782openalex-extracted

Machine Learning Based Photovoltaics (PV) Power Prediction Using Different Environmental Parameters of Qatar

inferredcites →https://doi.org/10.3390/en12244749openalex-extracted

Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules

inferredcites →https://doi.org/10.4229/27theupvsec2012-4do.5.1openalex-extracted

Technology and Climate Trends in PV Module Degradation

inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-extracted

Scikit-learn: Machine Learning in Python

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inferred← citeshttps://doi.org/10.1016/j.renene.2025.123685openalex-snapshot

A machine learning approach to PV-climate classification

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.