Zobrazeno 1 - 10
of 1 682
pro vyhledávání: '"square support vector machine"'
Development of an Optimized Ensemble Least Squares Model for Identifying Potential Deposit Customers
Publikováno v:
Journal of Applied Engineering and Technological Science, Vol 6, Iss 1 (2024)
The banking sector faces significant challenges in effectively promoting its products and services. While direct marketing has proven to be a potent tool for customer acquisition, it often leads to customer dissatisfaction, thereby tarnishing the ban
Externí odkaz:
https://doaj.org/article/3e6d986e0d0b4e06b878fd765dd944d5
Autor:
Farah Anishah Zaini, Mohamad Fani Sulaima, Intan Azmira Wan Abdul Razak, Mohammad Lutfi Othman, Hazlie Mokhlis
Publikováno v:
Algorithms, Vol 17, Iss 11, p 510 (2024)
Accurate electricity demand forecasting is crucial for ensuring the sustainability and reliability of power systems. Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. However, the less optima
Externí odkaz:
https://doaj.org/article/4620ffde1e2b4e409f9ba62ee0140000
Publikováno v:
Cybernetics and Information Technologies, Vol 23, Iss 1, Pp 125-140 (2023)
Every country must have an accurate and efficient forecasting model to avoid and manage the epidemic. This paper suggests an upgrade to one of the evolutionary algorithms inspired by nature, the Barnacle Mating Optimizer (BMO). First, the exploration
Externí odkaz:
https://doaj.org/article/a3adccbfdaf54e939b8f08ab67e684c0
Autor:
Mohamed El Amine Ben Seghier, Hermes Carvalho, Caroline Correa de Faria, José A.F.O. Correia, Ricardo Hallal Fakury
Publikováno v:
Alexandria Engineering Journal, Vol 67, Iss , Pp 489-502 (2023)
This study presents an advanced framework for modeling the lateral-torsional buckling behavior of cellular steel beams, which combines hybrid intelligent models with numerical simulation. The proposed hybrid intelligent models employ a large dataset-
Externí odkaz:
https://doaj.org/article/900bac3c22f447bfbd2599f6a329280d
Autor:
Yee Cai Ning, Syahrir Ridha, Suhaib Umer Ilyas, Shwetank Krishna, Iskandar Dzulkarnain, Muslim Abdurrahman
Publikováno v:
Journal of Petroleum Exploration and Production Technology, Vol 13, Iss 4, Pp 1031-1052 (2022)
Abstract A detailed understanding of the drilling fluid rheology and filtration properties is essential to assuring reduced fluid loss during the transport process. As per literature review, silica nanoparticle is an exceptional additive to enhance d
Externí odkaz:
https://doaj.org/article/d6f5e44d3b374dff8d406790c6fdfe5d
Publikováno v:
Gong-kuang zidonghua, Vol 48, Iss 12, Pp 79-85 (2022)
The underground coal mine environment is complex. The existing coal mine robot positioning methods have low positioning precision and low real-time performance caused by the non-line-of-sight (NLOS) error and other factors. In order to solve the abov
Externí odkaz:
https://doaj.org/article/98e74d37b4a74f61990bc65cb216a72a
Autor:
Rana Muhammad Adnan Ikram, Hong-Liang Dai, Ahmed A. Ewees, Jalal Shiri, Ozgur Kisi, Mohammad Zounemat-Kermani
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 12063-12080 (2022)
For better estimation of renewable environmental friendly and carbon-free energy resources, precise prediction of solar energy is very essential. However, accurate prediction of solar energy is a challenging task due to its fluctuations and due to cl
Externí odkaz:
https://doaj.org/article/2be5018d43f5441f94f4b8745ce96883
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 2859-2874 (2022)
This paper presents a new multi-objective optimization dispatching method to optimize the output power of distributed generators of a micro-grid considering uncertainty in wind power forecasting with the aims of minimizing the operational cost and po
Externí odkaz:
https://doaj.org/article/aaa54bad1de041779e0867a82733f2a8
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 9899-9918 (2022)
The intermittency and randomness of wind speed time series influence the forecasting accuracy. To figure out this problem and enhance the forecasting performance, a novel compound structure is developed for short-term wind speed forecasting. The deve
Externí odkaz:
https://doaj.org/article/d9f0077e1990413a9e5c54b83e4c65b7
Publikováno v:
水下无人系统学报, Vol 30, Iss 5, Pp 550-557 (2022)
The algorithms currently applied to state of health(SOH) estimation require numerous data samples for training and the estimation effect is not good. To address this issue, this study proposed a least-squares support vector machine(LSSVM) algorithm b
Externí odkaz:
https://doaj.org/article/a9fe7b2257f74286a2581fd0f1a84f9a