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Your search keyword '"Wongsinlatam, Wullapa"' showing total 3 results
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3 results on '"Wongsinlatam, Wullapa"'

1. Manipulation of Hidden Layers to Improve the Generalization Ability of Neural Networks.

Author

Wongsinlatam, Wullapa

Subjects
*ARTIFICIAL neural networks, *BACK propagation, *GENERALIZATION, *MATHEMATICAL regularization, *LAPLACE distribution
Abstract

This paper proposed a new algorithm (IM-COH) which was developed based on backpropagation algorithm on neural network (BPNN). This kind of algorithm improved the generalization ability on neural networks to optimize its structure in regularization method. The IM-COH algorithm controls the outputs of nodes in the hidden layers which were manipulated to eliminate the distribution weights problem and enhance the ability to move toward target problems. Furthermore, the IM-COH algorithm maintains the ability to reduce the random noise in the input sample. In this research, the IM-COH algorithm is simulated with two-spiral classification problem and Mackey-Glass time series prediction to compare with Gaussian regularizer (GR) and Laplace regularizer (LR). The results show that the generalization ability of the IM-COH algorithm is better than GR and LR in testing data samples and noise data. In addition, the IM-COH algorithm performs better in solving the two-spiral classification problem comparing to Mackey-Glass time series prediction. [ABSTRACT FROM AUTHOR]

Published
2016
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2. Electrical performance enhancement of a triboelectric nanogenerator based on epoxy resin/BaTiO3 by Al nanopowder addition for low power electronic devices.

Author

Amorntep, Narong, Namvong, Ariya, Wongsinlatam, Wullapa, Remsungnen, Tawun, Siritaratiwat, Apirat, Srichan, Chavis, Sriphan, Saichon, Pakawanit, Phakkhananan, Ariyarit, Atthaporn, Supasai, Wisut, Jutong, Nuttachai, Narkglom, Sorawit, and Surawanitkun, Chayada

Subjects
*ELECTRONIC equipment, *RENEWABLE energy sources, *ENERGY dispersive X-ray spectroscopy, *EPOXY resins, *POWDERS, *INTELLIGENT sensors, *ELECTRON energy loss spectroscopy, *SMART materials
Abstract

Triboelectric nanogenerators (TENGs) are crucial for applications such as smart sensors and bio-electronics. In the current work, we aimed for improved performance of TENGs with incorporation of BaTiO3 powder, which is known for its strong ferroelectric properties, combining it with epoxy resin to improve the flexibility of our devices. We observed that our TENGs can operate for over 24 000 cycles with no degradation of function. Additionally, we improved the electrical performance of the TENGs by incorporating various aluminum concentrations that change the electronic properties in the form of mixed epoxy resin, BaTiO3, and Al nanopowders. To identify the optimum conditions for the best performance, we analyzed the electrical characteristics and material properties by employing scanning electron microscopy, energy dispersive x-ray spectroscopy, and x-ray diffractometry characterization techniques. Our findings suggest that this innovative combination of materials and optimization techniques can significantly improve the performance of TENGs, making them ideal for practical applications in various fields, such as low-power electronics, environmental monitoring and healthcare. Moreover, these enhanced TENGs can serve as sustainable and dependable energy sources for various applications. [ABSTRACT FROM AUTHOR]

Published
2023
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3. Transmission Network Expansion Planning with High-Penetration Solar Energy Using Particle Swarm Optimization in Lao PDR toward 2030.

Author

Keokhoungning, Thongsavanh, Premrudeepeechacharn, Suttichai, Wongsinlatam, Wullapa, Namvong, Ariya, Remsungnen, Tawun, Mueanrit, Nongram, Sorn-in, Kanda, Kravenkit, Satit, Siritaratiwat, Apirat, Srichan, Chavis, Khunkiti, Sirote, and Surawanitkun, Chayada

Subjects
*PARTICLE swarm optimization, *ENERGY consumption, *RELIABILITY in engineering, *SOLAR energy, *TEST systems
Abstract

The complexity and uncertainty of power sources connected to transmission networks need to be considered. Planners need information on the sustainability and economics of transmission network expansion planning (TNEP). This work presents a newly proposed method for TNEP that considers high-penetration solar energy by using the particle swarm optimization (PSO) algorithm. The power sources, thermal and hydropower plants, and conditions of load were set in the account, including an uncertain power source and solar energy (PV). The optimal sizing and locating of the PV to be connected to the network were determined by the PSO. The PV grid code was set in the account. The new line's investment cost and equipment was analyzed. The PV cost was considered based on the power loss, and the system's reliability was improved. The IEEE 118 bus test system and Lao PDR's system were requested to test the proposed practice. The results demonstrate that the proposed TNEP method is robust and feasible. The simulation results will be applied to guide the power system planning of Lao PDR. [ABSTRACT FROM AUTHOR]

Published
2022
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