Publications

Teaching Mathematical Modelling for Earth Sciences via Case Studies

Engineering & Information Technology

3d Numerical Modelling of Cracking and Fragmentation in Percussive Drilling Using Fdem

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Nonlinear finite element 3-D simulations of CFRP shear strengthening

A binary PSO based ensemble under-sampling model for rebalancing imbalanced training data

Ensemble technique and under-sampling technique are both effective tools used for imbalanced dataset classification problems. In this paper, a novel ensemble method combining the advantages of both ensemble learning for biasing classifiers and a new under-sampling method is proposed. The under-sampling method is named Binary PSO instance selection; it gathers with ensemble classifiers to find the most suitable length and combination of the majority class samples to build a new dataset with minority class samples. The proposed method adopts multi-objective strategy, and contribution of this method is a notable improvement of the performances of imbalanced classification, and in the meantime guaranteeing a best integrity possible for the original dataset. We experimented the proposed method and compared its performance of processing imbalanced datasets with several other conventional basic ensemble methods. Experiment is also conducted on these imbalanced datasets using an improved version where ensemble classifiers are wrapped in the Binary PSO instance selection. According to experimental results, our proposed methods outperform single ensemble methods, state-of-the-art under-sampling methods, and also combinations of these methods with the traditional PSO instance selection algorithm.

A binary PSO-based ensemble under-sampling model for rebalancing imbalanced training data

No abstract is provided for this article.

Trigonometry

Trigonometry is an essential part of engineering mathematics. For example, in robotics, trigonometry can be useful in calculating the positions of robotic arms, rotations as well as other quantities. In addition, trigonometrical functions are also intrinsically related to complex numbers. This chapter introduces the fundamentals of trigonometrical functions.

Nature-Inspired Clustering Algorithms for Web Intelligence Data.

From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms

Nature has provided rich models for computational problem solving, including optimizations based on the swarm intelligence exhibited by fireflies, bats, and ants. These models can stimulate computer scientists to think nontraditionally in creating tools to address application design challenges.

Bat Algorithm is Better Than Intermittent Search Strategy

The efficiency of any metaheuristic algorithm largely depends on the way of balancing local intensive exploitation and global diverse exploration. Studies show that bat algorithm can provide a good balance between these two key components with superior efficiency. In this paper, we first review some commonly used metaheuristic algorithms, and then compare the performance of bat algorithm with the so-called intermittent search strategy. From simulations, we found that bat algorithm is better than the optimal intermittent search strategy. We also analyse the comparison results and their implications for higher dimensional optimization problems. In addition, we also apply bat algorithm in solving business optimization and engineering design problems.

Cellular Automata Networks

A small-world cellular automaton network has been formulated to simulate the long-range interactions of complex networks using unconventional computing methods in this paper. Conventional cellular automata use local updating rules. The new type of cellular automata networks uses local rules with a fraction of long-range shortcuts derived from the properties of small-world networks. Simulations show that the self-organized criticality emerges naturally in the system for a given probability of shortcuts and transition occurs as the probability increases to some critical value indicating the small-world behaviour of the complex automata networks. Pattern formation of cellular automata networks and the comparison with equation-based reaction-diffusion systems are also discussed

The Value of Information: Assessing the Ability of Electrical Resistivity to Detect CO2 Leakage in a Shallow Aquifer

List of contributors

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List of contributors

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Proceedings of Eighth International Congress on Information and Communication Technology

No abstract is provided for this article.

Benchmark Problems in Structural Optimization

No abstract is provided for this article.

Fibre-reinforced polymer strengthenir

The use of fiber-reinforced polymer (FRP) shear strengthening systems for the strength enhancement of existing reinforced concrete structures is discussed. An experimental and analytical research programme is under way to investigate the performance of bonded passive and unbonded prestressed FRP shear systems, and to quantify the effect of the load history on the strengthed behavior. Non-linear finite-element analysis are being developed to model the strengthed behavior. The results will provide insight into the optimum system parameters and contribute to the formulation of design guidance for advanced FRP strengthing strategies.

Parameterless Bat Algorithm and Its Performance Study

No abstract is provided for this article.