Dinh-Nhat Truong

• Ph.D
• PhD Student at National Taiwan University of Science and Technology

Reinforced concrete (RC) flat slabs, a popular choice in construction due to their flexibility, are susceptible to sudden and brittle punching shear failure. Existing design methods often exhibit significant bias and variability. Accurate estimation of punching shear strength in RC flat slabs is crucial for effective concrete structure design and m...

Real-world optimization problems are ubiquitous across scientific domains, and many engineering challenges can be reimagined as optimization problems with relative ease. Consequently, researchers have focused on developing optimizers to tackle these challenges. The Snake Optimizer (SO) is an effective tool for solving complex optimization problems,...

This paper presents a novel fuzzy adaptive jellyfish search-optimized stacking system (FAJS-SS) that integrates the jellyfish search (JS) optimizer, the fuzzy adaptive (FA) logic controller, and stacking ensemble machine learning. First, FA logic is incorporated into JS optimizer to construct an efficient metaheuristic algorithm for global optimiza...

The cover image is based on the Research Article Identifying deflections of reinforced concrete beams under seismic loads by bio‐inspired optimization of deep residual learning by Jui‐Sheng Chou et al., https://doi.org/10.1002/stc.2918

Real estate is one of the most critical investments in the household portfolio, and represents the greatest proportion of wealth of the private households in highly developed countries. This research provides a comprehensive review of machine learning techniques for predicting house prices. Data on dwelling transaction prices in Taipei City were co...

The seismic performance of a building must be evaluated after it has been affected by an earthquake load. In the evaluation process, building codes and standards require that the drift of the structure is determined to assess structural performance. This study provides an innovative method that helps engineers in measuring the deflection of reinfor...

A multi-objective forensic-based investigation (MOFBI) algorithm is developed to solve engineering optimization problems with multiple objectives. In the proposed algorithm, a chaotic map is used to initialize the population; Lévy flight, two elite populations, and a fixed-size archive are used to operate the motions of investigators and police off...

The fiber-reinforcement of soil is an effective and reliable ground improvement technique for increasing the strength and stability of soil for various purposes (including retaining structures, embankments, foundations, slopes, and pavements). Numerous scholars have developed methods to identify factors that influence the shear strength and to pred...

To increase the efficiency of energy use, ensure the stability of the power supply, and achieve balance in the energy supply, power management units have proposed plans that integrate energy-saving with intelligent systems, in which smart grids are used to distribute power and to manage power consumption. Imagery deep learning technology is propose...

Machine learning techniques have been used to develop many regression models to make predictions based on experience and historical data. They might be used singly or in ensembles. Single models are either classification or regression models that use one technique, while ensemble models combine various single models. To construct or find the best m...

This study aims to develop a novel forecasting system that optimizes linear time-series with nonlinear machine learning models to identify the historical pattern of regional energy consumption. The linear time-series model, Seasonal AutoRegressive Integrated Moving Average (SARIMA), was applied to simulate the linear component, while the least squa...

This study develops a novel metaheuristic algorithm that is motivated by the behavior of jellyfish in the ocean and is called artificial Jellyfish Search (JS) optimizer. The simulation of the search behavior of jellyfish involves their following the ocean current, their motions inside a jellyfish swarm (active motions and passive motions), a time c...

This study develops a Multi-Objective Jellyfish Search (MOJS) algorithm to solve engineering problems optimally with multiple objectives. Lévy flight, elite population, fixed-size archive, chaotic map, and the opposition-based jumping method are integrated into the MOJS to obtain the Pareto optimal solutions. These techniques are employed to define...

Multi-Objective Jellyfish Search (MOJS) Algorithm with Benchmark Functions

This work develops a novel metaheuristic optimization-based least squares support vector regression (LSSVR) model with a multi-output (MO) algorithm for assessing natural hazards. The MO algorithm is more efficient than the single-output algorithm because the relations among outputs can be estimated simultaneously by the proposed prediction model....

By providing a range of values rather than a point estimate, accurate interval forecasting is critical to the success of investment decisions in exchange rate markets. This work proposes a slidingwindow metaheuristic optimization for interval-valued time series forecasting using multi-output least squares support vector regression (MLSSVR). The hyp...

The main goal of the analysis of microbial ecology is to understand the relationship between Earth’s microbial community and their functions in the environment. This paper presents a proof-of-concept research to develop a bioclimatic modeling approach that leverages artificial intelligence techniques to identify the microbial species in a river as...

The Taiwan high-speed rail (HSR) markedly reduces the travel time from the north of Taiwan to the south, or vice versa, relative to other modes of public overland transportation. The HSR is faster than those modes, but also more expensive to ride. The pricing of HSR tickets has gained limited public acceptance because it lacks justification, indica...