Three modified versions of passing vehicle search (PVS) are proposed and tested on truss topology optimization with static and dynamic constraints. PVS works on the mechanism of passing a vehicle on a two-lane highway...
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Three modified versions of passing vehicle search (PVS) are proposed and tested on truss topology optimization with static and dynamic constraints. PVS works on the mechanism of passing a vehicle on a two-lane highway. The heuristic nature of PVS allows the search to jump into non-visited regions (exploration) and also permits a local search of visited regions (exploitation). First, the original PVS algorithm is improved to avoid a local optima trap using a novel parallel run mechanism. Then, population diversity is improved by incorporating the selection of simulated annealing. The various versions of PVS are verified on the truss design problems. Comparative results show that the parallel run concept improves the original PVS algorithm. The selection using the Boltzmann probability as used in simulated annealing further improves the algorithm.
Many iterative reconstruction algorithms for electrical impedance tomography have been proposed and tested using simulated data. A comparison between measurements and the simulated model has found that there is a sign...
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Many iterative reconstruction algorithms for electrical impedance tomography have been proposed and tested using simulated data. A comparison between measurements and the simulated model has found that there is a significant difference. This prevents the reconstruction from giving meaningful practical results. By modifying the conventional iterative reconstruction algorithm, the difference has been reduced so that reasonable reconstructions can be obtained from the measured data.
Angular random walk and rate random walk are two dominant random noise components which are inherent in almost gyroscopes. Therefore, modelling these noise components accurately is very important. Here, a modified alg...
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Angular random walk and rate random walk are two dominant random noise components which are inherent in almost gyroscopes. Therefore, modelling these noise components accurately is very important. Here, a modified algorithm is proposed for estimating the two random noise components accurately. Up to now, the statistical modelling of the two random noise components has been conducted by the best linear unbiased estimator, which is based on the formulae for mean, variance and covariance of non-overlapping Allan variance of them, that is, angular random walk and rate random walk. The modified algorithm is developed by using the best linear unbiased estimator, based on formulae for mean, variance and covariance of fully-overlapping Allan variance which are newly derived in this paper. Efficiency of the algorithm is evaluated by simulation and experiment.
A series of paroxysmal events have occurred unceasingly around the world in recent years, and delivering the relief supplies to disaster areas in the shortest time is becoming a difficult problem in emergency logistic...
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A series of paroxysmal events have occurred unceasingly around the world in recent years, and delivering the relief supplies to disaster areas in the shortest time is becoming a difficult problem in emergency logistics distribution system. A multi-mode layered network is introduced in this paper according to the function of nodes of emergency logistics networks, such as emergency logistics centre and demand centres, in the process of material circulation. Then, we design a multi-mode layered network to describe the behaviour of emergency supply transportation. On this basis, an objective function of emergency vehicles scheduling is proposed by analysing the constraints in the emergency logistics process, and a linear programming model based on an improved idea of maximum flow minimum cost is used to solve this problem. Finally, this model is calculated and analysed through a concrete example. The results show that the model is encouraging and can solve the issues of both urgency of transit time and the feature of road capacity in real life.
The multilayer perceptrons (MLPs) have been widely used in many communication applications, however, the learning process of the multilayer perceptrons often becomes very slow, which is due to the existence of the sin...
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ISBN:
(纸本)9781538635247
The multilayer perceptrons (MLPs) have been widely used in many communication applications, however, the learning process of the multilayer perceptrons often becomes very slow, which is due to the existence of the singularities in the parameter space. As the singularities significantly affect the learning dynamics of MLPs, the standard gradient descent method is not Fisher efficient. In order to overcome this problem, natural gradient method and adaptive natural gradient method were proposed to accelerate the learning process. As is well known, step size in each iteration plays a key role in the performance of algorithms. In this paper, the modified adaptive natural gradient method is proposed where the step size in each iteration is adaptive modified. The aim of the proposed algorithm is to accelerate the convergence speed and increase the performance of MLPs. The simulation results verify the validity of the analytical results.
The deployment of Wireless Sensor Network(WSN) must be done with some kind of advanced techniques so that it can mitigate the energy constraints. An existing, clustered-based routing protocol known as Low-Energy Adapt...
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ISBN:
(纸本)9781479956869
The deployment of Wireless Sensor Network(WSN) must be done with some kind of advanced techniques so that it can mitigate the energy constraints. An existing, clustered-based routing protocol known as Low-Energy Adaptive Clustering Hierarchy (LEACH) was studied, the outcome is an improved algorithm based on LEACH. The performance of these algorithms was studied through simulations using OMNeT++. In the original LEACH, the Cluster Heads selections were based on a distributed algorithm. For the modified algorithm, the improvement was done in the Cluster Head selection process. The selection process takes into account the residual energy of each node and used its probability outcome for the determination of the threshold value for next round. The results concluded that the performance of the modified algorithm is better than the original LEACH, the outcome will result in maximizing network lifetime.
Atrial fibrillation is a type of atria arrhythmia which can cause the formation of blood clot in the heart. The blood clot may enlarge or moving to the brain and cause stroke. Therefore, this study monitors the perfor...
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ISBN:
(纸本)9781479940844
Atrial fibrillation is a type of atria arrhythmia which can cause the formation of blood clot in the heart. The blood clot may enlarge or moving to the brain and cause stroke. Therefore, this study monitors the performance of ECG episodes for paroxysmal atrial fibrillation classification. Episode of 2 seconds to 8 seconds were used to observe the performance of electrocardiograph (ECG) signal processing of atrial fibrillation patient classification. Methods of features extraction were based on the concept of describing short-term behaviour of complex physical and biological system, namely second order system (SOS), and with modified algorithm (hybrid with fast-Fourier transform, FFT). Features extracted from the ECG signal of atrial fibrillation patient were defined using three parameters, i.e. natural frequency, forcing input and damping coefficient. A total of twelve parameters were observed. Comparisons of performance between length of ECG episodes were explored for SOS, FFT-SOS and SOS-FFT algorithms. The episode of 4 seconds using SOS algorithm provides the highest accuracy (98 %) during the classification of ECG signal.
Based on a modified Newton method in the Banach algebra of square matrices, we construct here a simple iterative algorithm that converges to the unique positive solution of the algebraic Riccati equation XCX=D. Numeri...
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Based on a modified Newton method in the Banach algebra of square matrices, we construct here a simple iterative algorithm that converges to the unique positive solution of the algebraic Riccati equation XCX=D. Numerical examples illustrating the theoretical study and showing the speed of convergence of our approach are discussed as well. At the end, we put some open questions as purposes for future research.
In this paper, an unsupervised learning algorithm called the modified fuzzy min-max neural network for clustering on the application of the pipeline internal inspection data (MFNNC) is proposed. As the original fuzzy ...
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This paper propounds a modified version of the salp swarm algorithm (mSSA) for solving optimization problems more prolifically. This technique is refined from the base version with three simple but effective modificat...
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This paper propounds a modified version of the salp swarm algorithm (mSSA) for solving optimization problems more prolifically. This technique is refined from the base version with three simple but effective modifications. In the first one, the most important parameter in SSA responsible for balancing exploration and exploitation is chaotically changed by embedding a sinusoidal map in it to catch a better balance between exploration and exploitation from the first iteration until the last. As a short falling, SSA can't exchange information amongst leaders of the chain. Therefore, a mutualistic relationship between two leader salps is included in mSSA to raise its search performance. Additionally, a random technique is systematically applied to the follower salps to introduce diversity in the chain. This can be since there may be some salps in the chain that do not necessarily follow the leader for exploring unvisited areas of the search space. Several test problems are solved by the advocated approach and results are presented in comparison with the relevant results in the available literature. It is ascertained that mSSA, despite its simplicity, significantly outperforms not only the basic SSA but also numerous recent algorithms in terms of fruitful solution precision and convergent trend line.
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