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We propose a novel regression, which is called Twin Support Vector Regression (TSVR) to improve the precision of indoor positioning. Similar as Support Vector Regression (SVR), there are 6 parameters to be identified. However, compared with SVR, less computation time and approximate performance can be achieved with TSVR. Genetic Algorithm (GA) is used to avoid local optimum in indoor positioning to...
The partner selection and optimization problem is an important area of virtual enterprise (VE). Genetic algorithm (GA) is optimization and parallel strategy simulating biology evolutionary mechanism in nature and a high efficient algorithm solving these types of problems. After analyzing the partner selection problems of virtual enterprise, the improved genetic algorithm (IGA) was presented to solve...
Focusing on the non-stationary characteristic of the fault signal of subway auxiliary inverter, this paper proposes the method that combines ensemble empirical mode decomposition (EEMD) with genetic algorithm to optimize BP neural network (GABP) to diagnose the fault categories of subway auxiliary inverter. Firstly, this paper extracts feature vectors from the original fault signal by EEMD, then establishes...
With the increasing demand of electric power, transmission congestion becomes a popular phenomenon in power systems. In order to improve the ATC (Available Transfer Capability) between buses of the network, this paper proposes a location method of TCSC in power grid. Power transfer distribution factor and line outage distribution factor are used to build the mathematical model of ATC considering the...
Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Through discussing the sequential approach, which is the classical asynchronous multisensor data fusion algorithm, a new algorithm based on distributed computation structure is proposed. The...
According to the bottleneck process- copper electroplating of the repair process for continuous casting crystallizer copper, a genetic algorithm is designed to solve its scheduling problem, including the coding, the decoding, the crossover and mutation. Through the analysis of simulation experiments, compared with the use of the manual mode and the heuristic algorithm, the genetic algorithm shows...
Tool inventory has a large difference with the traditional static inventory since the tool can be reused by grinding. In this paper, according to the life characteristics of tool, the tool inventory cost model has been built by studying the using process of tool. The model takes all costs which includes the shortage cost in the product life cycle into account under the circumstances of demand uncertainty...
The classification performance of Support Vector Machine (SVM) is heavily influenced by its kernel parameter g and penalty factor c. in this paper, Cross-validation (CV) based grid-search optimization, CV-based genetic algorithm (GA) and CV-based particle swarm optimization (PSO) are respectively used for parameters optimization in SVM for fault classification of inverters in traction converter. Simulation...
This paper investigates the vehicle routing problem (VRP) under multi-objective constraints. More specifically, we consider the distance, fixed cost, time, together with risk simultaneously. To get a quicker and more accurate solution, several improvements are proposed in applying GA for optimization search. Practical test confirms the effectiveness of the proposed method.
Vehicle scheduling problem of urban bus line is complex and involves multiple objectives. Currently, existing approaches incorporate those objectives in a linear fashion to form a single objective and then use a single objective optimization approach to solve it. However, these approaches can only produce one solution and it is not easy to assign a proper weight for each objective to get a superior...
Fuzzy supervisory predictive control based on genetic algorithm optimization is proposed. For the nonlinear model, through a general objective function dynamically optimized to determine the optimal set-point for a given regulatory level, by using genetic algorithm in order to solve the nonlinear optimization problem for the setpoint, and compared with the supervisory predictive control based on linear...
It is worse that steam generator is controlled by PID which is non-minimum system with oscillation. ADRC achieves excellent control performance using nonlinear control law, but it isn't necessarily optimal when adopting standard ADRC structure and NLSEF. In this paper, we optimize the standard ADRC, the simplified ADRC without TD, the improved ADRC with NLSEF using mtfal and zzxfal based on GA. The...
Reverse E-auction has been widely applied to the centralized E-procurement of governments and large enterprise groups recently. In this paper, a multi-item procurement problem with variable quantities is investigated and the organization process of the corresponding reverse E-auction is introduced. The winner determination problem (WDP), which plays an important role in the investigated problem, is...
There is a huge energy-saving space in sports lighting area, sports lighting designers have taken plenty of measures to save energy, but using the intelligent optimization algorithms to optimize the sports lighting's light environment for energy-saving are rarely studied in domestic. In this paper we take advantage of the evolutionary parallel search abilities of genetic algorithms to find the appropriate...
The structure of traditional distribution network is changed from a single supply radial network to a more power ring network when grid is connected with distributed generations (DG), and island phenomenon occurs higher in the process of reconstruction, which becomes uncontrolled and high risk operation and increased the difficulty of distribution network reconstruction. The improved immune genetic...
This article uses the novelty and applicability of adaptive genetic algorithms for the development of advanced digital radio frequency memory jammer technology uses radar CFAR detection algorithm. As a major result, demonstrates how adaptive genetic algorithms can produce effective single-resistant interference. This is an important attribute when interference uncertain radar detection algorithms...
To guarantee success of precision navigation, it is necessary to carry out in-field calibration for the accelerometers of platform inertial navigation system (INS) before a mission is launched. Traditional continuous self-calibration methods are not fit for accelerometers' fast calibration because the platform misalignments have to be estimated precisely and the nonlinear coupling terms will affect...
The design objectives of PID controller is to choose the reasonable parameters which can make the system meet the design requirements. Specific to the problem of the controller parameter optimization of flight control system, the classic tuning method of PID controller parameters is cumbersome and need repeating trial. What's more, the controller parameters cannot be guaranteed to be optimal. Therefore,...
This paper studies the fault diagnosis of inertia navigation unit which plays an important role in inertia navigation system. The method chosen in the fault diagnosis is combined Genetic Algorithm and wavelet neural network. Wavelet transform will effectively handle the collected inertia navigation unit signal. The characteristic signals extracted will be regarded as inputs to the neural network....
Based on analysis of plate shape defect pattern in cold rolling, a defect recognition method using RBF-BP combinational neural network model optimized by genetic algorithm is proposed in this paper. The method makes use of genetic algorithm to optimize the weights and thresholds of the input layer, hidden layer and output layer in the RBF-BP network, and a GA-RBF-BP network model is formed. It can...
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