Accurate R-peak detection is very important for arrhythmia diagnosis. Our previous effective R detection algorithm consisted of three strategies: band-pass filter, adaptive definition of interesting block and dynamic ...
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ISBN:
(纸本)9781538691847
Accurate R-peak detection is very important for arrhythmia diagnosis. Our previous effective R detection algorithm consisted of three strategies: band-pass filter, adaptive definition of interesting block and dynamic threshold. Then, it adopted the optimization algorithm to replace the knowledge-based theory and found out the suitable parameters (El, F2, N, WI, W2, beta and mu) in R detection algorithm quickly and obtained the high performance of detecting R peaks (99.77%). In order to improve the performance of the previous study, this study proposes to add the median filter in the algorithm to correct baseline wander components of electrocardiography (ECG) signals. It is necessary to defined two parameters (Ti and T2) in median filter. Therefore, this study adopts particle swarm optimization (PSO) to find the suitable parameters (Ti, T2, F1, F2, N, W1, W2, beta and mu) in the proposed method. The proposed method is applied to MIT-BIH arrhythmia database. The results show that PSO can find out the suitable parameters in R detection algorithm and have a higher accuracy (99.95%) than one of the previous study.
This paper studies the optimization problem of PCB assembly time for multi-head placement machine. Mathematical model is built and analyzed for the problem, which is of a combinatorial nature and computationally intra...
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ISBN:
(纸本)9781538629185
This paper studies the optimization problem of PCB assembly time for multi-head placement machine. Mathematical model is built and analyzed for the problem, which is of a combinatorial nature and computationally intractable. An optimization algorithm based on heuristic strategy and scatter search method is proposed to minimize the PCB assembly time. By relaxing the restrictions on the problem, the algorithm reduces the assembly time by minimizing cycles of pick-and-place, constructing the simultaneous pickups and optimizing sequence of pick-and-place of components. Numerical experiments were conducted to evaluate the proposed algorithm, along with a comparison with a heuristic algorithm(HA) under strong constraints proposed in existed literature. The results show that the proposed algorithm has better performance in optimization results and can shorten PCB assembly time of multi-head placement machine effectively.
In this paper, a new Pigeon Colony algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process,...
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In this paper, a new Pigeon Colony algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution;the flying process is designed to search for the local and global optimum and improve the global worst solution;and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.
After the reference of straight line stability control strategy of four-wheel drive vehicle, this paper proposes a control algorithm combining the sliding mode variable structure and optimization control method. The c...
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After the reference of straight line stability control strategy of four-wheel drive vehicle, this paper proposes a control algorithm combining the sliding mode variable structure and optimization control method. The control algorithm is mainly divided into the upper generalized moment calculation based on the sliding mode variable structure controller and the lower torque distribution controller based on the optimization algorithm, also including the slip rates controller based on PID algorithm to ensure the straight line stability control. This paper establishes the combined model based on the CarSim and MATLAB, and tests to verify the validation of the control strategy through the four-wheel drive vehicle test-bed based on RT_LAB. The simulation and experimental results show that when the tire-road friction coefficient is low, the control strategy can not only make the vehicle tire slip rates stay near the optimal slip ratio, at the same time through the yawing moment adjustment, ensure the yaw angle of vehicle not beyond 0.5 deg/s, so the method can effectively ensure the straight line stability of four wheel drive vehicle. (C) 2016 Published by Elsevier Ltd.
Accurate dual-axis sun tracking is the key feature of a heliostat and is critical for the performance of a solar tower power plant. The primary tracking errors with respect to the geometrical errors could be theoretic...
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Accurate dual-axis sun tracking is the key feature of a heliostat and is critical for the performance of a solar tower power plant. The primary tracking errors with respect to the geometrical errors could be theoretically determined from the measurements of the BCS based on optimization algorithm. Tests are performed on two heliostats in DAHAN solar tower plant and analyses are performed to evaluate the comprehensive effect of the six angular geometrical errors on the heliostat tracking accuracy. The test results show that the altitude-azimuth tracking angle formulas for several fixed geometrical errors work well and have a effectiveness for a given period of time. (C) 2013 Zhifeng Wang. Published by Elsevier Ltd.
Heat dissipations of servers in datacenter racks are following an ever-increasing trend, breaking the economical heat removal limits of traditional air-based cooling technologies. Currently, an average of 40-45% of th...
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ISBN:
(纸本)9781728124612
Heat dissipations of servers in datacenter racks are following an ever-increasing trend, breaking the economical heat removal limits of traditional air-based cooling technologies. Currently, an average of 40-45% of the total datacenter energy consumption is needed to cool servers, presenting significant challenges to maintain energy efficiencies and also noise levels within US OSHA standards The present paper focuses on the determination of the optimal design of a compact plate heat exchanger (PHE), acting as an overhead refrigerant-to-water condenser of a macro-scale thermosyphon, which dissipates the total heat from a datacenter rack into a cooling loop for waste heat recovery applications (e.g. district heating network). PHEs are already the preferred solution for many industrial and domestic applications (especially small to medium size refrigeration and heat pump systems), since they provide higher heat transfer performance, higher flexibility toward the targeted application and lower pressure drops compared to the conventional tube-in-tube and shell-and-tube heat exchangers. Furthermore, due to the numerous variables involved in the design of PHEs, such as plate number, plate footprint size, geometry of the corrugation pattern (i.e. chevron angle, pressing depth, etc.), an optimization analysis and corresponding simulation tool is auspicious to finding the optimal design of these units to accommodate the targeted heat rates of datacenter racks. Hence, this study proposes a novel optimization process which incorporates a local simulator (an improved version compared to the one presented at ITHERM 2018) for accurately rating and designing PHEs over a wide range of operating conditions, plate geometries and working fluids. The improved simulator uses a local one-dimensional effectiveness-NTU approach, with a local implementation of mass, momentum and energy equations, coupled with newly upgraded methods for condensation heat transfer coefficients and frictional p
A novel Monte Carlo Tree Search optimization algorithm that is trained using a Reinforcement Learning approach is developed for the application to geometric design tasks. It is capable of evaluating design parameters ...
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ISBN:
(数字)9781624105951
ISBN:
(纸本)9781624105951
A novel Monte Carlo Tree Search optimization algorithm that is trained using a Reinforcement Learning approach is developed for the application to geometric design tasks. It is capable of evaluating design parameters and demonstrates the successful application of reinforcement learning strategies on a physics informed design optimization task. The algorithm is intended to be used for the parametric design of the optimal geometry of a propeller for Fixed-Wing VTOL UAV but is also applied to an aircraft design problem with ease.
This paper declares a Coyote optimization algorithm (COA)-based method of determining both optimal PV locations and sizes simultaneously in a distribution system with the largest hosting capacity (HC) of solar photovo...
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ISBN:
(纸本)9798350381061
This paper declares a Coyote optimization algorithm (COA)-based method of determining both optimal PV locations and sizes simultaneously in a distribution system with the largest hosting capacity (HC) of solar photovoltaic (PV) generation and minimizing system voltage deviation. The objective function includes PV hosting capacity (PVHC) and voltage deviation amplitude at each bus. The RMS bus voltage, the maximum size of each PV placement at an installed bus, the total active power losses, and reverse power flow at the substation are constraints to be met. The problem is solved using the Coyote optimization algorithm (COA). The IEEE 123-bus system is applied to test the proposed method. Results are compared with those obtained by other metaheuristic methods, including Genetic algorithm and Particle Swarm optimization. Test results show that the COA method yields exceptional solutions compare to GA and PSO methods in both optimality and convergence.
In this paper, an optimization algorithm based on membrane system is proposed for numerical optimization problems. In the proposed algorithm, we designed two mechanisms to simulate the movement of molecules in arbitra...
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ISBN:
(纸本)9781728124858
In this paper, an optimization algorithm based on membrane system is proposed for numerical optimization problems. In the proposed algorithm, we designed two mechanisms to simulate the movement of molecules in arbitrary direction and a certain direction to balance global exploration and local exploitation. To test the performance of the proposed algorithm, eight benchmark functions were chosen. The simulation results show that the proposed algorithm is more advantageous than other experimental algorithms in solving numerical optimization problems.
In this paper, a method which employs Modified Teaching-Learning Based optimization (MTLBO) algorithm is proposed to determine the optimal placement and size of Distributed Energy Resources (DERs) units in distributio...
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ISBN:
(纸本)9781479949816
In this paper, a method which employs Modified Teaching-Learning Based optimization (MTLBO) algorithm is proposed to determine the optimal placement and size of Distributed Energy Resources (DERs) units in distribution systems. DERs are commonly connected near the load in electric power distribution systems and include renewable energy sources such as wind and solar, fossil-fuel-based generation such as micro turbines, and other distributed energy storage elements. Loss minimization and voltage profile improvement as objective function and for every combination of DERs, impact indices, active and reactive losses and voltage profiles is studied on different load models. For all cases current injection distribution load flow method is used and tested on 84-bus Taiwan Power Company distribution system using MTLBO algorithm.
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