-
Research Article
Morphology and Rehabilitation Roles of Chomo Grass (Brachiaria humidicola) in Gully and Fragile Degraded Lands in Mana Sibu District, Western Ethiopia
Tola Geleta Jawi*
,
Wakjira Takala Dibaba,
Amsalu Tilahun Fite,
Obsu Hirko
Issue:
Volume 10, Issue 3, June 2025
Pages:
57-64
Received:
13 February 2025
Accepted:
17 April 2025
Published:
14 May 2025
Abstract: Degradation of fragile lands and gully formation are pressing challenges in Western Ethiopia, particularly in the Mana Sibu District. The integration of Chomo grass (Brachiaria humidicola), a stoloniferous perennial grass with strong adaptive and restorative properties, has shown promising potential for ecological restoration and soil conservation. This study aimed to characterize the morphological traits of Chomo grass across different age categories and assess its role in the sustainable rehabilitation of degraded landscapes. A randomized complete block design was employed to evaluate both above- and below-ground morphological traits, including plant height, stolon length, leaf sheath, root depth, and plant density. Results revealed statistically significant differences (p<0.001) in most traits across age groups, indicating rapid early development and increasing restoration capacity with plant age. The highest ground cover (98.67%) and root length (125 cm) were recorded in older stands, supporting its effectiveness in enhancing soil stability, vegetation recovery, and water retention. Field observations further confirmed Chomo grass’s role in stabilizing gullies and fragile lands, reducing erosion, and supporting livelihoods through fodder production. The study recommends the expansion of Chomo grass as a viable biological soil and water conservation strategy in degraded areas.
Abstract: Degradation of fragile lands and gully formation are pressing challenges in Western Ethiopia, particularly in the Mana Sibu District. The integration of Chomo grass (Brachiaria humidicola), a stoloniferous perennial grass with strong adaptive and restorative properties, has shown promising potential for ecological restoration and soil conservation....
Show More
-
Research Article
A Stacking-Based Ensemble Model for Short-Term Load Forecasting
Issue:
Volume 10, Issue 3, June 2025
Pages:
65-71
Received:
14 April 2025
Accepted:
15 May 2025
Published:
11 June 2025
DOI:
10.11648/j.ijeee.20251003.12
Downloads:
Views:
Abstract: Short-term load forecasting plays an important and indispensable role in the daily operation planning of power grid because it allows grid operators to predict electricity demand a few hours to one week in advance. Although statistics-based methods and machine learning-based methods have been widely used in short-term load forecasting, a single model may have difficulty capturing all underlying dynamics, causing reduced prediction accuracy. Therefore, a stacking-based ensemble model that improves prediction accuracy by integrating multiple base prediction models is proposed in this study for short-term load forecasting. Firstly, for data preprocessing, data normalization is used to scale the raw load data to a range of 0 to 1. Data imputation is used to ensure data integrity. Secondly, base prediction models including logistic regression, decision tree, random forest, multilayer perceptron, convolutional neural network, and long short-term memory are utilized to train the prediction models. Thirdly, the stacking-based ensemble learning method is utilized to integrate these base prediction models to further predict electric load. The results of comparative experiments and error analysis show that the stacking-based ensemble learning model outperforms the base prediction models for the majority of the evaluation metrics. Additionally, the analysis of curve fitting results demonstrates the high level of agreement between the actual values and the predicted values for the stacking-based ensemble learning model.
Abstract: Short-term load forecasting plays an important and indispensable role in the daily operation planning of power grid because it allows grid operators to predict electricity demand a few hours to one week in advance. Although statistics-based methods and machine learning-based methods have been widely used in short-term load forecasting, a single mod...
Show More
-
Research Article
The Impact of Renewable Energy Consumption on Inclusive Growth in Egypt
Issue:
Volume 10, Issue 3, June 2025
Pages:
72-91
Received:
15 April 2025
Accepted:
28 April 2025
Published:
19 June 2025
DOI:
10.11648/j.ijeee.20251003.13
Downloads:
Views:
Abstract: Inclusive growth is a central objective of sustainable development priorities, especially in developing countries that suffer from poverty and uneven income distribution. In light of the global trend towards reducing emissions and achieving environmental sustainability, renewable energy has emerged as a strategic tool to promote long-term economic and social growth. In this context, this research seeks to analyze the impact of renewable energy consumption on inclusive growth in Egypt during the period from 1990 to 2024, while including a set of influential economic and institutional variables. The study relied on an endogenous growth model, estimated using the extended ARDL methodology, along with boundary tests and error correction model, to measure the relationship between renewable energy consumption and inclusive growth represented by the Human Development Index (HDI). Explanatory variables included non-renewable energy, trade openness, rule of law as well as dummy variables reflecting the impact of the 2011 revolution and economic reforms. The results showed a long-run equilibrium relationship between renewable energy consumption and inclusive growth, with renewable energy contributing positively to the improvement of the HDI. The results also revealed a stronger and more pronounced impact of non-renewable energy on growth, indicating Egypt's continued reliance on traditional sources to support public services and raise the standard of living. On the other hand, the rule of law showed a negative impact on inclusive growth in the long run, which may be related to the effects of transitional legal reforms. Trade openness was negatively correlated with the Human Development Index, reflecting the unbalanced social effects of trade liberalization policies. The study recommends that investment in renewable energy should be directly linked to human development strategies, enhancing the efficiency of law enforcement institutions, and activating social protection programs to ensure that the transition to clean energy is supportive of social justice and inclusive growth.
Abstract: Inclusive growth is a central objective of sustainable development priorities, especially in developing countries that suffer from poverty and uneven income distribution. In light of the global trend towards reducing emissions and achieving environmental sustainability, renewable energy has emerged as a strategic tool to promote long-term economic ...
Show More
