Amir H Gandomi

Amir H Gandomi
University of Technology Sydney | UTS · Faculty of Engineering and Information Technology

Professor of Data Science

About

514
Publications
196,951
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
26,521
Citations
Additional affiliations
July 2019 - present
University of Technology Sydney
Position
  • Professor (Full)
May 2018 - June 2018
University of Paris-Est
Position
  • Professor
August 2017 - June 2019
Stevens Institute of Technology
Position
  • Professor (Assistant)

Publications

Publications (514)
Article
In this paper, a novel method is proposed for damage detection of structures with closely-spaced eigenvalues. The proposed method uses a transformed form of the condensed frequency response function matrix each of whose columns is obtained as the sum of the unwrapped instantaneous Hilbert phase of the corresponding decomposed column of the original...
Article
Because of the high competition among IT sectors, companies are planning to migrate to the cloud for effective growth and development. Driven by the importance of the cloud, new cloud vendors emerge each day to satisfy the demand of IT sectors. As a result, selection of an apt cloud vendor is critical. To this end, researchers have proposed differe...
Article
Full-text available
Flood management in a reservoir-outlet system is a multi-criterion decision-making (MCDM) issue, in which preventing flood damage and flood overtopping, as well as fulfilling water demands, are often considered essential practices. However, although MCDM models can be used for flood control, there is a knowledge gap in hybrid modeling of the reserv...
Preprint
The next release problem (NRP) refers to implementing the next release of software in the software industry regarding the expected revenues; specifically, constraints like limited budgets indicate that the total cost corresponding to the next software release should be minimized. This paper uses and investigates the comparative performance of ninet...
Article
In this paper, a systematic machine learning strategy is proposed to classify wood properties based on a contact ultrasonic testing results. As such, several aspects of the wood material including the type of wood (hardwood or softwood), the direction of an ultrasonic test with respect to the growth rings of the wood, and, whether the wood is damag...
Preprint
Nowadays, human activity recognition (HAR) is a key component of many ubiquitous innovative solutions, where both accelerometer and gyroscope data provide information about an observed person's physical activity. HAR offers a diverse variety of important applications, including healthcare, burglary detection, workplace monitoring, and emergency det...
Article
Full-text available
This study proposes a new nature-inspired metaheuristic that mimics the behaviour of the prairie dogs in their natural habitat called the prairie dog optimization (PDO). The proposed algorithm uses four prairie dog activities to achieve the two common optimization phases, exploration and exploitation. The prairie dogs’ foraging and burrow build act...
Preprint
Full-text available
Soil erosion is a significant threat to the environment and long-term land management around the world. Accelerated soil erosion by human activities inflicts extreme changes in terrestrial and aquatic ecosystems, which is not fully surveyed/predicted for the present and probable future at field-scales (30-m). Here, we estimate/predict soil erosion...
Article
Full-text available
The multiphase shock wave phenomenon is significantly affected by accumulated upstream sediment deposition and downstream hydraulic conditions. There is a lack of studies evaluating the efficacy of intelligent models in representing multiphase debris flooding over initially dry- or wet-bed tail-waters, or over downstream semi-circular obstacles. To...
Article
Timber has been widely utilized as a type of green material in the construction industry. However, the anisotropic and highly heterogeneous nature of timber increases the difficulty of damage identification, which is critical for maintaining structures in which it is used. In this paper, we propose a timber damage identification dynamic broad netwo...
Chapter
Particle Swarm Optimization (PSO) is a nature-inspired optimizer that has attracted a lot of attention since its inception in 1995 due to its ease of application and promising results. The inspiration of PSO is the collaborative swarm behavior of biological populations—a noted computational intelligence technique. There is no doubt that PSO has mad...
Chapter
Optimization problems can be observed in many applications, ranging from engineering applications and decision-making to computer science and finance. Optimization can be described as a process for discovering optimal solution among all available solutions of the defined problem, considering complex and high-dimensional constraints in searching for...
Article
The evaluation of slope stability of a three-dimensional slope requires identifying the critical slip surface with the minimum factor of safety, which is a complex optimization problem. Failure to identify the critical slip surface can lead to unconservative conclusions about the stability of a slope. This paper proposes a novel 3D surface-altering...
Article
Background and objectives The prediction of multiple drug efficacies using machine learning prediction techniques based on clinical and molecular attributes of tumors is a new approach in the field of precision medicine of oncology. The selection of suitable and effective therapeutic drugs among the potential drugs is performed computationally cons...
Article
Acute Lymphoblastic Leukemia (ALL) is cancer in which bone marrow overproduces undeveloped lymphocytes. Over 6500 cases of ALL are diagnosed every year in the United States in both adults and children, accounting for around 25% of pediatric cancers, and the trend continues to rise. With the advancements of AI and big data analytics, early diagnosis...
Article
Full-text available
This study proposes the Fire Hawk Optimizer (FHO) as a novel metaheuristic algorithm based on the foraging behavior of whistling kites, black kites and brown falcons. These birds are termed Fire Hawks considering the specific actions they perform to catch prey in nature, specifically by means of setting fire. Utilizing the proposed algorithm, a num...
Article
Full-text available
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that simulates the hunting behavior of hawks. This swarm-based optimizer performs the optimization procedure using a novel way of exploration and exploitation and the multiphases of search. In this review research, we focused on the applications and developments of the...
Chapter
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book defines automation and data collection methods. It provides a discussion of the general structure and macroarchitecture of the development of infrastructure models at the network level as well as the main components of the overall...
Chapter
The use of image processing tools generates data for analysis, which in many cases, and requires the use of fuzzy methods to remove ambiguity or quantification. Fuzzy rules and fuzzy reasoning are essential components of fuzzy inference systems that are the most important modeling elements based on fuzzy set concept and are widely used in the analy...
Chapter
This chapter examines the structure and architecture of automated infrastructure inspection equipment, and presents a set of final criteria expected from advanced upgrades. It introduces some emerging technologies that can be effective in increasing the efficiency of the automation evaluation, inspection, and technology development process in this...
Chapter
Nature‐inspired optimization algorithms (NIOA) are a set of algorithms that are inspired by the behavior of natural phenomena, such as simulating congestion intelligence, biological systems, and physical and chemical systems. This chapter summarizes the main theory and general idea of some NIOAs and presents detail on how to use one or more NIOAs....
Chapter
This chapter presents the basic principles and working methods of diagnosis and new effective parameters in diagnosing failure or anomaly. It introduces various methods for automatic detection of anomalies in infrastructure, including road paving, that can be further developed for other infrastructure, such as tunnel walls, structures, dams, silos,...
Chapter
The key goal of applying image‐processing techniques is to extract meaningful features in order to perform classification and evaluation operations. Extracting features with more data transfer capability can increase the speed and efficiency of the method. This chapter examines the types of feature extraction methods and image‐related features. The...
Chapter
Feature selection is an important step to reduce dimensions, whereby less important features are removed and ultimately limited to a small subset of main features. This chapter presents the latest developments in various feature selection methods. It examines filter, wrapper, and hybrid methods utilizing a combination of different methods through e...
Chapter
The three main components for any automated system are: image capture device, image analysis system and related algorithms, and interpretation and indexing methods. This chapter deals with the second part of automated systems, namely image processing. Each analysis of an image requires six general steps, which include: preprocessing, segmentation,...
Chapter
This chapter presents the performance evaluation methods and indicators, and provides a summary of the types of general indicators in infrastructure evaluation. It provides a general classification of the performance evaluation methods and common indicators. The chapter presents a general category of evaluation metrics that includes General statist...
Chapter
Classification is a type of prediction and calculation method in which a method is designed to guess the placement of data in a category, whereby the output is categorized and a class is located. This chapter describes the most common classification methods used in infrastructure management and provides examples of applications. It presents the fol...
Article
Full-text available
Establishing a holistic approach to managing floods and droughts is essential considering the different hydrological conditions. This work aimed to demonstrate how the integrated management of floods and droughts (IMFD) can increase sustainability and decrease the vulnerability of reservoirs against water-related disasters. To do so, a non-integrat...
Article
The determination of the compression index (Cc) of clay through oedometer tests is time-consuming and expensive. To replace the practice of conducting laboratory oedometer tests, this study presents a comparative analysis of hybrid machine learning models for estimating the soil Cc based on actual laboratory test data. Ten swarm intelligence algori...
Preprint
Full-text available
To solve complex real-world problems, heuristics and concept-based approaches can be used in order to incorporate information into the problem. In this study, a concept-based approach called variable functioning Fx is introduced to reduce the optimization variables and narrow down the search space. In this method, the relationships among one or mor...
Article
Full-text available
Wireless sensor networks (WSNs) comprise several cooperating sensor nodes capable of sensing, computing, and transmitting sensed signals to a central server. This research proposes a sensor system-based network with low power communication using swarm intelligence integrated with multi-hop communication (SIMHC). This routing protocol selects the op...
Article
Full-text available
The process of designing the support system of a subway station using a concrete arch pre-supporting system (CAPS) construction method includes an estimation of design variables based on intuition and experience. However, this process may often lead to controversial and economically unfavorable designs. In this regard, developing an optimization mo...
Article
Full-text available
Background and objectives Over the past two decades, medical imaging has been extensively apply to diagnose diseases. Medical experts continue to have difficulties for diagnosing diseases with a single modality owing to a lack of information in this domain. Image fusion may be use to merge images of specific organs with diseases from a variety of m...
Conference Paper
Full-text available
A novel methodology based on the Bayesian Model Averaging (BMA) method was employed to combine predictions of three individual expert systems; Support Vector Regression (SVR), Generalized Regression Neural Networks (GRNNs), and Multi-layer Perceptron (MLP). The BMA model has the capacity to evaluate different model predictions and assign each one o...
Preprint
Full-text available
This manuscript introduces a new socio-inspired metaheuristic technique referred to as Leader-Advocate-Believer based optimization algorithm (LAB) for engineering and global optimization problems. The proposed algorithm is inspired by the AI-based competitive behaviour exhibited by the individuals in a group while simultaneously improving themselve...
Code
The source codes of Starling Murmuration Optimizer (SMO) Article: Starling murmuration optimizer: A novel bio-inspired algorithm for global and engineering optimization https://www.researchgate.net/publication/358570414_Starling_murmuration_optimizer_A_novel_bio-inspired_algorithm_for_global_and_engineering_optimization
Code
Starling murmuration optimizer (SMO) for solving CEC 2017 test functions
Article
Full-text available
The exposition of any nature-inspired optimization technique relies firmly upon its executed organized framework. Since the regularly utilized backtracking search algorithm (BSA) is a fixed framework, it is not always appropriate for all difficulty levels of problems and, in this manner, probably does not search the entire search space proficiently...
Article
Big data analytics in healthcare is emerging as a promising field to extract valuable information from large databases and enhance results with fewer costs. Although numerous methods have been proposed for big data analytics in the medical field, an authorized entity is required to access data, inhibiting diagnosis accuracy and efficiency. Particul...
Preprint
Full-text available
Advancements in smart vehicle design have enabled the creation of Internet of Vehicle (IoV) technologies that can utilize the information provided by various sensors and wireless communication to perform complex functionality. Many of these functionalities rely on high computational power and low latency. Mobile Edge Computing (MEC) technologies ha...
Article
Full-text available
In this study, sustainable mixture designs of three concrete types, including fly ash concrete, silica fume concrete, and ground granulated blast furnace slag concrete, were investigated. To this end, the compressive strength formulas of each concrete type made with supplementary cementitious materials were obtained by introducing a new machine lea...
Article
Full-text available
Groundwater management is essential in water and environmental engineering from both quantity and quality aspects due to the growing urban population. Groundwater vulnerability evaluation models play a prominent role in groundwater resources management, such as the DRASTIC model that has been used successfully in numerous areas. Several studies hav...
Article
Full-text available
Real-world engineering design problems are widespread in various research disciplines in both industry and industry. Many optimization algorithms have been employed to address these kinds of problems. However, the algorithm’s performance substantially reduces with the increase in the scale and difficulty of problems. Various versions of the optimiz...
Article
Applications of machine learning (ML) methods have been used extensively to solve various complex challenges in recent years in various application areas, such as medical, financial, environmental, marketing, security, and industrial applications. ML methods are characterized by their ability to examine many data and discover exciting relationships...
Article
Full-text available
Floods are a natural disaster of significant concern because of their considerable damages to people’s livelihood. To this extent, there is a critical need to enhance the flood management techniques through establishing proper infrastructures, such as detention basins. However, although intelligent models may be adopted for flood management by dete...
Data
Dataset #3: Herein, 24 distinct video files have been presented which related to dam-break multiphase flood shock wave experiments, performed ‒ in the Shiraz University, Civil and Environmental Engineering Department’s Hydraulic Lab (Shiraz, Iran) ‒ using a 6-m-long horizontal laboratory flume with prismatic rectangular section; 0.3 m wide and 0.32...
Data
Dataset #1: Herein, 27 distinct video files have been presented which related to dam-break multiphase flood shock wave experiments, performed ‒ in the Shiraz University, Civil and Environmental Engineering Department’s Hydraulic Lab (Shiraz, Iran) ‒ using a 6-m-long horizontal laboratory flume with prismatic rectangular section; 0.3 m wide and 0.32...
Data
Dataset #2: Herein, 24 distinct video files have been presented which related to dam-break multiphase flood shock wave experiments, performed ‒ in the Shiraz University, Civil and Environmental Engineering Department’s Hydraulic Lab (Shiraz, Iran) ‒ using a 6-m-long horizontal laboratory flume with prismatic rectangular section; 0.3 m wide and 0.32...
Data
Dataset #4: Herein, 24 distinct video files have been presented which related to dam-break multiphase flood shock wave experiments, performed ‒ in the Shiraz University, Civil and Environmental Engineering Department’s Hydraulic Lab (Shiraz, Iran) ‒ using a 6-m-long horizontal laboratory flume with prismatic rectangular section; 0.3 m wide and 0.32...
Article
This paper presents a novel bio-inspired algorithm inspired by starlings' behaviors during their stunning murmuration named starling murmuration optimizer (SMO) to solve complex and engineering optimization problems as the most appropriate application of metaheuristic algorithms. The SMO introduces a dynamic multi-flock construction and three new s...
Article
Full-text available
Problems like improper sampling (sampling on unnecessary variables) and undefined prior distribution (or taking random priors) often occur in model updating. Any such limitations on model parameters can lead to lower accuracy and higher experimental costs (due to more iterations) of structural optimisation. In this work, we explored the effective d...
Code
This is the alpha version of the INFO optimizer. The source codes of this algorithm are publicly available at https://aliasgharheidari.com/INFO.html. This code presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weight...
Article
The study proposes an improved Harris hawks optimization (IHHO) algorithm by integrating the standard Harris hawks optimization (HHO) algorithm and mutation-based search mechanism for developing a high-performance machine learning solution for predicting soil compression index. HHO is a newly introduced meta-heuristic optimization algorithm (MOA) u...
Article
In the last decade, the application of membrane-inspired evolutionary algorithms in real-life problems has attracted much attention due to their flexibility and parallelizability. Almost seven years have passed since the first membrane algorithms survey paper was published in 2014. Considering the importance and ongoing research on such algorithms...
Article
Full-text available
Edge computing has received significant attention from academia and industries and has emerged as a promising solution for enhancing the information processing capability at the edge for next generation 6G networks. The technical design of 6G edge networks in terms of offloading the computationally extensive task is very critical because of the ove...
Article
Full-text available
There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease‐19 (COVID‐19). We aimed to a) identify complement‐related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether com...
Article
A novel highly robust-to-noise and closely-situated eigenvalues damage detection method is proposed. The proposed method employs the Variational Mode Decomposition (VMD) to construct a new set of input signals obtained from the rows of the condensed Frequency Response Function (CFRF) to be used in a sensitivity-based model updating problem. Each ro...
Data
Herein, 150 distinct video files have been presented which related to dam-break multiphase flood shock wave experiments, performed in the Shiraz University, Civil and Environmental Engineering Department’s Hydraulic Lab (Shiraz, Iran). A clear water reservoir (without sediment) as well as 7 different sediment depths (0.03, 0.075, 0.15, 0.175, 0.2,...
Data
In this file, all sediment depth data associated with 21 different dam break scenarios were extracted from high-quality experimental video images. The dataset is collected, classified and presented in a total of 21 distinct tables in 3 categories based on downstream initial conditions: 1- Downstream bed with a semi-circular obstacle with radius of...
Data
In this file, all water level data associated with 24 different dam break scenarios were extracted from high-quality experimental video images. The dataset is collected, classified and presented in a total of 24 distinct tables in 3 categories based on downstream initial conditions: 1- Downstream bed with a semi-circular obstacle with radius of 4.5...
Data
The source codes and all files of this algorithm are publicly available at https://aliasgharheidari.com/INFO.html. This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weighted mean idea is employed for a sol...
Article
Full-text available
The source codes of this algorithm are publicly available at https://aliasgharheidari.com/INFO.html. This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weighted mean idea is employed for a solid structure a...
Article
Full-text available
Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. Computational Intelligence (CI) techniques have been recognized as effective methods in generating and optimizing renewable tools. The complexity of this variety of energy depends on its coverage of large sizes of data and parameter...