Estimating the global solar irradiation and optimizing the error estimates under Algerian desert climate

Bouchouicha, Kada; Hassan, Muhammed A.; Bailek, Nadjem; Aoun, Nouar

doi:10.1016/j.renene.2019.02.071

Cited by 53 publications

(18 citation statements)

References 47 publications

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“…A ∈ N is defined as the set of all reference nodes and mobile agent nodes, where (a ' , a, k) ∈ A represents the reference node. The agent node and any node in the network (Bouchouicha et al 2019). A group of communication and measurement topology nodes to and from the network agent node a at time t represents Ca, Ma, and t, respectively, and the adjacent communication nodes kεCa, t, Ca, and t are a subset of A. Ca, t ⊆ A\(a) represents the adjacent measurement node k∈Ma, t, and Ma; t is Ma; t ⊆ A \(a) is a subset of A.…”

Section: Distributed Mobile Agent Cooperative Positioning Modelmentioning

confidence: 99%

RETRACTED ARTICLE: Mountain soil characteristics and agrotourism management optimization based on distributed collaboration

Zhanhui

2021

Arab J Geosci

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This article uses the distributed collaborative neural network process for analysis. It turns out that if there are dishonest participants, they will not get any data. The dishonest participants did not contribute to the training process throughout the training process, but they could get the training results of others. In order to understand the seasonal dynamics of soil organic carbon components and mineralization in different altitudes of alpine shrub meadows, the effects of different mountain soil carbon components on soil organic carbon mineralization were discussed, and the relationship between soil carbon components and soil physical and chemical properties was analyzed. This plays an important role in the development of dynamic changes of soil organic carbon in alpine mountain shrub meadows at different altitudes. In this study, a combination of field investigation and indoor analysis was used. By taking the soil of 3,800 m, 4000 m, and 4200 m semi-shady slope and semi-sun slope as the object of this research, it explored the different heights, seasons, and indoor cultivation conditions. The characteristics of mountain soil carbon minerals under the changing conditions of soil organic carbon pool. In this article, we take leisure agriculture and rural tourism development and management optimization as the research goal of this time, based on the sustainable development theory of leisure agriculture and rural tourism development. Using literature methods and on-site surveys, the research results of domestic and foreign scholars are collected, starting from the concept of leisure agriculture and rural tourism, and using the past experience of domestic and foreign leisure agriculture and leisure rural tourism development to analyze the current domestic and foreign leisure agriculture and the relationship between rural tourism development.

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Section: Distributed Mobile Agent Cooperative Positioning Modelmentioning

confidence: 99%

RETRACTED ARTICLE: Mountain soil characteristics and agrotourism management optimization based on distributed collaboration

Zhanhui

2021

Arab J Geosci

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“…Mean Square Error [3,11] Root Mean Square Error RMSE RMSE = √ MSE [3,[9][10][11]18,20,25,26,[28][29][30]34] Normalized RMSE nRMSE nRMSE = RMSE GH I 0 [7][8][9][10][11]18,19,22,23,25,28,30,34] Mean Bias Error [3,[9][10][11]18,20,25,[28][29][30]34] Normalized MBE nMBE nMBE = MBE GH I 0 [7,8,10,11,18,21,23,25,30,34] Mean Absolute Error [3,11,21,…”

Section: Abbreviation Expression Referencesmentioning

confidence: 99%

A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application

et al. 2020

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The increasing integration of photovoltaic (PV) power plants into power systems demands a high accuracy of yield prediction and measurement. With this aim, different global horizontal irradiance (GHI) estimations based on new-generation geostationary satellites have been recently proposed, providing a growing number of solutions and databases, mostly available online, in addition to the many ground-based irradiance data installations currently available. According to the specific literature, there is a lack of agreement in validation strategies for a bankable, satellite-derived irradiance dataset. Moreover, different irradiance data sources are compared in recent contributions based on a diversity of arbitrary metrics. Under this framework, this paper describes a characterization of metrics based on a principal component analysis (PCA) application to classify such metrics, aiming to provide non-redundant and complementary information. Therefore, different groups of metrics are identified by applying the PCA process, allowing us to compare, in a more extensive way, different irradiance data sources and exploring and identifying their differences. The methodology has been evaluated using satellite-based and ground-measured GHI data collected for one year in seven different Spanish locations, with a one-hour sample time. Data characterization, results, and a discussion about the suitability of the proposed methodology are also included in the paper.

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“…In most aforementioned papers, the climate variables are used to estimate solar radiation on a horizontal plane, or the horizontal solar radiation is used as an input variable to estimate radiation on a tiled surface [15][16][17]. In this paper, we estimated hourly tilted solar irradiation using climate variables.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Ensemble-Learning Approach for Renewable Energy Resources Evaluation in Algeria

El-kenawy¹,

Ibrahim²,

Bailek³

et al. 2022

Computers, Materials &Amp; Continua

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In order to achieve a highly accurate estimation of solar energy resource potential, a novel hybrid ensemble-learning approach, hybridizing Advanced Squirrel-Search Optimization Algorithm (ASSOA) and support vector regression, is utilized to estimate the hourly tilted solar irradiation for selected arid regions in Algeria. Long-term measured meteorological data, including mean-air temperature, relative humidity, wind speed, alongside global horizontal irradiation and extra-terrestrial horizontal irradiance, were obtained for the two cities of Tamanrasset-and-Adrar for two years. Five computational algorithms were considered and analyzed for the suitability of estimation. Further two new algorithms, namely Average Ensemble and Ensemble using support vector regression were developed using the hybridization approach. The accuracy of the developed models was analyzed in terms of five statistical error metrics, as well as the Wilcoxon rank-sum and ANOVA test. Among the previously selected algorithms, K Neighbors Regressor and support vector regression exhibited good performances. However, the newly proposed ensemble algorithms exhibited even better performance. The proposed model showed relative root mean square errors lower than 1.448% and correlation coefficients higher than 0.999. This was further verified by benchmarking the new ensemble against several popular swarm intelligence algorithms. It is concluded that the proposed algorithms are far superior to the commonly adopted ones.

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Estimating the global solar irradiation and optimizing the error estimates under Algerian desert climate

Cited by 53 publications

References 47 publications

RETRACTED ARTICLE: Mountain soil characteristics and agrotourism management optimization based on distributed collaboration

RETRACTED ARTICLE: Mountain soil characteristics and agrotourism management optimization based on distributed collaboration

A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application

Hybrid Ensemble-Learning Approach for Renewable Energy Resources Evaluation in Algeria

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