Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (109)
  • Open Access

    ARTICLE

    GIS analysis of hypsometry and basin asymmetry factor in Htab river basin and tectonic implications (Central Atlas, Tunisia)

    Ali Chaieb, Noamen Rebai

    Revue Internationale de Géomatique, Vol.29, No.3, pp. 287-296, 2019, DOI:10.3166/rig.2019.00082

    Abstract The geomorphology of the Htab river watershed is mainly guided by the action of the E-W Kasserine fault. This activity influenced the installed hydrographic system. To see the impact of neotectonic on the Htab river watershed, four morphometric indices were applied: the elongation ratio, the hypsometric curve, the hypsometric integral, and the asymmetry factor. The processing and calculation of these indices were based on global DEMs (Digital Elevation Models). The result obtained shows an important link between the activity of the Kasserine fault, the geomorphological behavior of the Htab river watershed and the hydrographic network. Field observations confirmed well these… More >

  • Open Access

    ARTICLE

    PSO-BP-Based Optimal Allocation Model for Complementary Generation Capacity of the Photovoltaic Power Station

    Zhenfang Liu*, Haibo Liu, Dongmei Zhang

    Energy Engineering, Vol.120, No.7, pp. 1717-1727, 2023, DOI:10.32604/ee.2023.027968

    Abstract To improve the operation efficiency of the photovoltaic power station complementary power generation system, an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed. Particle Swarm Optimization and BP neural network are used to establish the forecasting model, the Markov chain model is used to correct the forecasting error of the model, and the weighted fitting method is used to forecast the annual load curve, to complete the optimal allocation of complementary generating capacity of photovoltaic power stations. The experimental results show that this method reduces the average loss of photovoltaic output… More >

  • Open Access

    ARTICLE

    PREDICTING THE WAX DEPOSITION RATE BASED ON EXTREME LEARNING MACHINE

    Qi Zhuanga,* , Zhuo Chenb, Dong Liuc, Yangyang Tiand

    Frontiers in Heat and Mass Transfer, Vol.19, No.1, pp. 1-8, 2022, DOI:10.5098/hmt.19.19

    Abstract In order to improve the accuracy and efficiency of wax deposition rate prediction of waxy crude oil in pipeline transportation, A GRA-IPSO-ELM model was established to predict wax deposition rate. Using Grey Relational Analysis (GRA) to calculate the correlation degree between various factors and wax deposition rate, determine the input variables of the prediction model, and establish the Extreme Learning Machine (ELM) prediction model, improved particle swarm optimization (IPSO) is used to optimize the parameters of ELM model. Taking the experimental data of wax deposition in Huachi operation area as an example, the prediction performance of the model is evaluated… More >

  • Open Access

    ARTICLE

    Optimal Management of Energy Storage Systems for Peak Shaving in a Smart Grid

    Firas M. Makahleh1, Ayman Amer2, Ahmad A. Manasrah1, Hani Attar2, Ahmed A. A. Solyman3, Mehrdad Ahmadi Kamarposhti4,*, Phatiphat Thounthong5

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3317-3337, 2023, DOI:10.32604/cmc.2023.035690

    Abstract In this paper, the installation of energy storage systems (EES) and their role in grid peak load shaving in two echelons, their distribution and generation are investigated. First, the optimal placement and capacity of the energy storage is taken into consideration, then, the charge-discharge strategy for this equipment is determined. Here, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to calculate the minimum and maximum load in the network with the presence of energy storage systems. The energy storage systems were utilized in a distribution system with the aid of a peak load shaving approach. Ultimately, the battery… More >

  • Open Access

    ARTICLE

    BN-GEPSO: Learning Bayesian Network Structure Using Generalized Particle Swarm Optimization

    Muhammad Saad Salman1, Ibrahim M. Almanjahie2,3, AmanUllah Yasin1, Ammara Nawaz Cheema1,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4217-4229, 2023, DOI:10.32604/cmc.2023.034960

    Abstract At present Bayesian Networks (BN) are being used widely for demonstrating uncertain knowledge in many disciplines, including biology, computer science, risk analysis, service quality analysis, and business. But they suffer from the problem that when the nodes and edges increase, the structure learning difficulty increases and algorithms become inefficient. To solve this problem, heuristic optimization algorithms are used, which tend to find a near-optimal answer rather than an exact one, with particle swarm optimization (PSO) being one of them. PSO is a swarm intelligence-based algorithm having basic inspiration from flocks of birds (how they search for food). PSO is employed… More >

  • Open Access

    ARTICLE

    Dynamic Allocation of Manufacturing Tasks and Resources in Shared Manufacturing

    Caiyun Liu, Peng Liu*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3221-3242, 2023, DOI:10.32604/iasc.2023.035114

    Abstract Shared manufacturing is recognized as a new point-to-point manufacturing mode in the digital era. Shared manufacturing is referred to as a new manufacturing mode to realize the dynamic allocation of manufacturing tasks and resources. Compared with the traditional mode, shared manufacturing offers more abundant manufacturing resources and flexible configuration options. This paper proposes a model based on the description of the dynamic allocation of tasks and resources in the shared manufacturing environment, and the characteristics of shared manufacturing resource allocation. The execution of manufacturing tasks, in which candidate manufacturing resources enter or exit at various time nodes, enables the dynamic… More >

  • Open Access

    ARTICLE

    An Optimization Capacity Design Method of Wind/Photovoltaic/Hydrogen Storage Power System Based on PSO-NSGA-II

    Lei Xing1, Yakui Liu2,3,*

    Energy Engineering, Vol.120, No.4, pp. 1023-1043, 2023, DOI:10.32604/ee.2023.025335

    Abstract The optimal allocation of integrated energy system capacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy, which has attracted many attentions. However, the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters. To solve the above problem, the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms. Firstly, an integrated energy system consisting of the photovoltaic, wind turbine, electrolysis cell, hydrogen storage tank, and energy storage is established. Meanwhile, the minimum economic cost, the maximum wind and PV power consumption rate, and the… More >

  • Open Access

    ARTICLE

    Comparative Analysis of Equal and Unequal Grounding Grid Configurations by Compression Ratio and Least Square Curve Fitting Techniques

    M. Soni*, Abraham George

    Energy Engineering, Vol.120, No.3, pp. 597-616, 2023, DOI:10.32604/ee.2023.021301

    Abstract The primary aim of the power system grounding is to safeguard the person and satisfying the performance of the power system to maintain reliable operation. With equal conductor spacing grounding grid design, the distribution of the current in the grid is not uniform. Hence, unequal grid conductor span in which grid conductors are concentrated more at the periphery is safer to practice than equal spacing. This paper presents the comparative analysis of two novel techniques that create unequal spacing among the grid conductors: the least-square curve fitting technique and the compression ratio technique with equal grid configuration for both square… More >

  • Open Access

    ARTICLE

    An Efficient Hybrid Optimization for Skin Cancer Detection Using PNN Classifier

    J. Jaculin Femil1,*, T. Jaya2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2919-2934, 2023, DOI:10.32604/csse.2023.032935

    Abstract The necessity of on-time cancer detection is extremely high in the recent days as it becomes a threat to human life. The skin cancer is considered as one of the dangerous diseases among other types of cancer since it causes severe health impacts on human beings and hence it is highly mandatory to detect the skin cancer in the early stage for providing adequate treatment. Therefore, an effective image processing approach is employed in this present study for the accurate detection of skin cancer. Initially, the dermoscopy images of skin lesions are retrieved and processed by eliminating the noises with… More >

  • Open Access

    ARTICLE

    DC–DC Converter with Pi Controller for BLDC Motor Fuzzy Drive System

    S. Pandeeswari1,*, S. Jaganathan2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2811-2825, 2023, DOI:10.32604/csse.2023.029945

    Abstract The Brushless DC Motor drive systems are used widely with renewable energy resources. The power converter controlling technique increases the performance by novel techniques and algorithms. Conventional approaches are mostly focused on buck converter, Fuzzy logic control with various switching activity. In this proposed research work, the QPSO (Quantum Particle Swarm Optimization algorithm) is used on the switching state of converter from the generation unit of solar module. Through the duty cycle pulse from optimization function, the MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) of the Boost converter gets switched when BLDC (Brushless Direct Current Motor) motor drive system requires power. Voltage Source… More >

Displaying 1-10 on page 1 of 109. Per Page  

Share Link