A Multi-Objective Mathematical Model for the Population-Based Transportation Network Planning

Chupradit, Supat; Tashtoush, Mohammad A.; Al-Mutta, Mohammed Yousif Oudah; Mahmudiono, Trias; Dwijendra, Ngakan Ketut Acwin; Chaudhary, Purnima; Ali, Muneam Hussein; Alkhayyat, Ahmed; Sutarto, Sutarto

doi:10.7232/iems.2022.21.2.322

Cited by 5 publications

(4 citation statements)

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“…Building on these related works, this research introduces improved neural network algorithms, including convolutional neural networks, recurrent neural networks, and attention mechanisms, to improve the performance and adaptability of fault detection in computer communication networks 8 . This research expects to provide stronger support for network stability and reliability, thus promoting further development in the field of network communications.…”

Section: Related Workmentioning

confidence: 99%

Studying computer communication networks to identify errors using enhanced neural network algorithms

zhang

2024

Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023)

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The stability and reliability of computer communication networks are crucial for the proper functioning of modern society. However, network faults are inevitable, so efficient fault detection systems are needed to quickly identify and solve problems. This study aims to improve the performance of network fault detection by introducing improved neural network algorithms and applying deep learning techniques to this field. First, we studied in detail the various types of faults that may occur in computer communication networks and constructed the corresponding fault datasets. Then, we introduced improved neural network structures, including convolutional neural networks and recurrent neural networks, to better capture the spatio-temporal characteristics of network data. Experimental results show that the improved neural network algorithm exhibits excellent performance in network fault detection. Compared with traditional methods, our model achieves significant improvements in detection rate and accuracy. In addition, the model demonstrates adaptability to different fault types, including traditional faults and emerging network threats. In summary, this study provides an efficient and reliable solution for fault detection in computer communication networks by introducing an improved neural network algorithm. This approach is expected to play an important role in real network operations and improve network stability and security, thus providing more reliable support for information communication in modern society.

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Section: Related Workmentioning

confidence: 99%

Studying computer communication networks to identify errors using enhanced neural network algorithms

zhang

2024

Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023)

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“…FCNs incorporate complex numbers into the support of a fuzzy set, resulting in a new type of fuzzy set with complex-valued membership functions. This idea was further extended in 2002 with the introduction of CFSs [30], which generalize the membership function of fuzzy sets from the unit interval [0, 1] to the unit disk in the complex plane. CFSs have been widely studied and applied by many researchers [31][32][33][34][35][36][37][38][39][40][41][42][43].…”

Section: Introductionmentioning

confidence: 99%

“…The modified Crank-Nicolson method for solving the fuzzy complex heat equation improves accuracy by considering fuzzy complex temperature values at the half-time step, effectively capturing uncertainties and imprecisions in a more precise manner compared to the classical Crank-Nicolson method [45][46][47][48]. The aim of this paper is focused on the fuzzification of complex fuzzy heat equation using the modified Crank-Nicolson method, where represented by two values (amplitude and phase terms) in the unit disk in the complex plane to provide the generalization and more accuracy for the solution of fuzzy heat equation by putting in the account of a new periodicity semantics that appears in the complex fuzzy information [30,43].…”

Section: Introductionmentioning

confidence: 99%

A Solution of the Complex Fuzzy Heat Equation in Terms of Complex Dirichlet Conditions Using a Modified Crank–Nicolson Method

Zureigat,

Tashtoush,

Jassar

et al. 2023

Advances in Mathematical Physics

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Complex fuzzy sets (CFSs) have recently emerged as a potent tool for expanding the scope of fuzzy sets to encompass wider ranges within the unit disk in the complex plane. This study explores complex fuzzy numbers and introduces their application for the first time in the literature to address a complex fuzzy partial differential equation that involves a complex fuzzy heat equation under Hukuhara differentiability. The researchers utilize an implicit finite difference scheme, namely the Crank–Nicolson method, to tackle complex fuzzy heat equations. The problem’s fuzziness arises from the coefficients in both amplitude and phase terms, as well as in the initial and boundary conditions, with the Convex normalized triangular fuzzy numbers extended to the unit disk in the complex plane. The researchers take advantage of the properties and benefits of CFS theory in the proposed numerical methods and subsequently provide a new proof of the stability under CFS theory. A numerical example is presented to demonstrate the proposed approach’s reliability and feasibility, with the results showing good agreement with the exact solution and relevant theoretical aspects.

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“…Thinking is formed by the interplay of surrounding elements such as time, situation or occasion, and subject. Thinking occurs in different forms and patterns (verbal, symbolic, quantitative, spatial, formal), each with its own specificity (Chupradit et al, 2022;Tashtoush et al, 2020 b).…”

Section: Introductionmentioning

confidence: 99%

The Synthetic Strategy and its Role to developing the Mathematical Creative Thinking Skills

Salem,

Kindi,

Mohammad

et al. 2023

ijmdsa

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This study aimed to investigate the role of the Synthetic Strategy on the development of mathematical creative thinking skills. The study sample consisted of (46) eighth-grade female students who were divided into two groups: an experimental group of (24) students taught linear equations using the Synthetic strategy, and a control group of (22) students taught using the traditional method. An experimental approach was employed, and a test for mathematical creative thinking was prepared. A pre-test and post-test were administered to both study groups, and their validity and reliability were confirmed. The Synthetic strategy was applied to teach solving linear equations. The results revealed a difference in the level of mathematical creative thinking in favor of the experimental group, and statistically significant differences were found between the mean scores of the two groups in mathematical creative thinking skills, which were attributed to the teaching strategy and in favor of the Synthetic strategy. Finally, the study recommended using the Synthetic strategy to teach linear equation and diversifying teaching strategies. It also suggested conducting further studies and research to explore the impact of different teaching strategies on the development of mathematical creative thinking skills.

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A Multi-Objective Mathematical Model for the Population-Based Transportation Network Planning

Cited by 5 publications

References 0 publications

Studying computer communication networks to identify errors using enhanced neural network algorithms

Studying computer communication networks to identify errors using enhanced neural network algorithms

A Solution of the Complex Fuzzy Heat Equation in Terms of Complex Dirichlet Conditions Using a Modified Crank–Nicolson Method

The Synthetic Strategy and its Role to developing the Mathematical Creative Thinking Skills

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