Sanghati Banerjee¹, Om Pal², Tauseef Ahmad³, Shruti Kanga⁴, Suraj Kumar Singh^1,*, Bhartendu Sajan¹

Revue Internationale de Géomatique, Vol.34, pp. 71-88, 2025, DOI:10.32604/rig.2025.057963 - 24 February 2025

Abstract Agriculture is a primary activity in many countries, with wheat being a major cereal crop in India. Accurate pre-harvest forecasts of crop acreage and production are critical for policymakers to address supply-demand dynamics, pricing, and trade. This study focuses on estimating wheat acreage and yield in Barwala block, Hisar district, Haryana, for the 2019–2020 Rabi season using remote sensing techniques. Multi-temporal satellite data capturing phenological stages of wheat (Seedling to Ripening) were processed using supervised classification with a maximum likelihood classifier in ERDAS Imagine. Wheat crop acreage was determined by overlaying ground truth points on… More >

Jiachang Liu^1,*, Zhengwei Huang², Junfeng Xiang¹, Lu Liu¹, Manlin Hu¹

Energy Engineering, Vol.121, No.11, pp. 3461-3486, 2024, DOI:10.32604/ee.2024.054514 - 21 October 2024

Abstract To enhance the refinement of load decomposition in power systems and fully leverage seasonal change information to further improve prediction performance, this paper proposes a seasonal short-term load combination prediction model based on modal decomposition and a feature-fusion multi-algorithm hybrid neural network model. Specifically, the characteristics of load components are analyzed for different seasons, and the corresponding models are established. First, the improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) method is employed to decompose the system load for all four seasons, and the new sequence is obtained through reconstruction based on the… More >

Jiana Chen^1,2, Fangbo Cao^1,2, Min Huang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 807-817, 2024, DOI:10.32604/phyton.2024.048299 - 29 April 2024

Abstract Transplanting rice varieties grown in different seasons can lead to different yields due to different dry matter production. Early-season rice varieties transplanted in the late season can obtain high yields with short-growth duration and higher yields driven by higher dry matter production. To make clear the variations in dry matter production across seasons, four early-season rice varieties were chosen for late-season transplantation. The grain yield, dry matter accumulation, leaf photosynthetic, and leaf stomatal properties were studied. It was observed that the average yields of these four varieties in the late season were 33% greater, despite… More >

Yang Li^1,2, Jianjun Zhao², Xiaolong Yang², He Wang^1,*, Yuyan Wang¹

Energy Engineering, Vol.121, No.5, pp. 1263-1289, 2024, DOI:10.32604/ee.2024.046784 - 30 April 2024

Abstract Distributed photovoltaic (PV) is one of the important power sources for building a new power system with new energy as the main body. The rapid development of distributed PV has brought new challenges to the operation of distribution networks. In order to improve the absorption ability of large-scale distributed PV access to the distribution network, the AC/DC hybrid distribution network is constructed based on flexible interconnection technology, and a coordinated scheduling strategy model of hydrogen energy storage (HS) and distributed PV is established. Firstly, the mathematical model of distributed PV and HS system is established,… More >

Lipei Chen, Rilie Deng, Xuewen Li, Min Yu, Hongdong Xiao^*

Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3359-3370, 2023, DOI:10.32604/phyton.2023.046877 - 28 December 2023

Abstract

In the rice-wheat rotation system, biochar (BC) can be applied at the initiation of the rice or wheat season. Here, we compared the effects of BC that were applied at two different crop seasons on wheat production, quality, and soil profile properties in a rice-wheat rotation system with nitrogen (N) fertilizer applied at 280 kg/ha rate. Results showed that both wheat grain production and N recovery use efficiency were influenced by BC applied at two crop seasons. Biochar application did not affect the total non-essential amino-acid, but when applied during wheat season, BC significantly (p

… More >

Yaping Luo¹, Na Guo^1,*, Dong Liu², Shuming Peng³, Xinchen Wang⁴, Jie Wu³

Revue Internationale de Géomatique, Vol.32, pp. 39-52, 2023, DOI:10.32604/RIG.2023.046014 - 20 December 2023

Abstract Using hyperspectral data collected in January and June 2022 from the Sha River, the concentrations of total nitrogen (TN) and total phosphorus (TP) were estimated using the differential method. The results indicate that the optimal bands for estimation vary monthly due to temperature fluctuations. In the TN model, the power function model at 586 nm in January exhibited the strongest fit, yielding a fit coefficient (R²) of 0.95 and F-value of 164.57 at a significance level (p) of less than 0.01. Conversely, the exponential model at 477 nm in June provided the best fit, with R² = More > Graphic Abstract

Shumin Sun¹, Peng Yu¹, Jiawei Xing¹, Yan Cheng¹, Song Yang¹, Qian Ai^2,*

Energy Engineering, Vol.120, No.12, pp. 2761-2782, 2023, DOI:10.32604/ee.2023.042635 - 29 November 2023

Abstract Wind power prediction is very important for the economic dispatching of power systems containing wind power. In this work, a novel short-term wind power prediction method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and (long short-term memory) LSTM neural network is proposed and studied. First, the original data is prepossessed including removing outliers and filling in the gaps. Then, the random forest algorithm is used to sort the importance of each meteorological factor and determine the input climate characteristics of the forecast model. In addition, this study conducts seasonal classification… More >

Louis F. Marie^*, Karina Sałek, Tadhg S. O’Donovan

Energy Engineering, Vol.120, No.10, pp. 2193-2209, 2023, DOI:10.32604/ee.2023.043075 - 28 September 2023

Abstract Composite thermochemical energy storage (TCES) represents an exciting field of thermal energy storage which could address the issue of seasonal variance in renewable energy supply. However, there are open questions about their performance and the root cause of some observed phenomena. Some researchers have observed the breakdown of particles in their production phase, and in their use. This study seeks to investigate the underlying cause of this breakdown. SEM and EDX analysis have been conducted on MgCl₂ impregnated 13X zeolite composites of differing diameters, as well as LiX zeolite. This was done in order to study… More > Graphic Abstract

Ahmed Salah^1,2, Mahmoud Bekhit³, Esraa Eldesouky^4,5, Ahmed Ali^4,6,*, Ahmed Fathalla⁷

Computer Systems Science and Engineering, Vol.46, No.1, pp. 445-460, 2023, DOI:10.32604/csse.2023.035254 - 20 January 2023

Abstract The price prediction task is a well-studied problem due to its impact on the business domain. There are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change, but there is very limited work to study the price prediction of seasonal goods (e.g., Christmas gifts). Seasonal items’ prices have different patterns than normal items; this can be linked to the offers and discounted prices of seasonal items. This lack of research studies motivates the current work to investigate the problem of seasonal items’ prices… More >

M. Mohan^1,*, P. C. Kishore Raja², P. Velmurugan³, A. Kulothungan⁴

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1151-1163, 2023, DOI:10.32604/iasc.2023.026255 - 06 June 2022

Abstract Prediction of stock market value is highly risky because it is based on the concept of Time Series forecasting system that can be used for investments in a safe environment with minimized chances of loss. The proposed model uses a real time dataset of fifteen Stocks as input into the system and based on the data, predicts or forecast future stock prices of different companies belonging to different sectors. The dataset includes approximately fifteen companies from different sectors and forecasts their results based on which the user can decide whether to invest in the particular… More >