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This paper uses the GA-SVM inversion model to invert the suspended matter concentration in Longquan Lake. Genetic algorithm (GA) optimizes the parameters of the SVM inversion model to establish the new GA-SVM inversion model, and GA can effectively improve the efficiency and the accuracy of the SVM inversion model. The inversion model was established by using the measured hyperspectral data and suspended...
The improved algorithm based on objective layered approach is used to deal with the multi-objective network optimization problem. Based on the traditional non-dominated sorting genetic algorithm, an improved algorithm is given. In order to increase the computational efficiency, the objective layered approach is used sort the individuals of population and identify the non-inferior solution. Individuals...
For compact multiple-input multiple-output (MIMO) active sensing applications, the issue of how to arrange the transmit and receive antenna elements in order to obtain a sparse linear array configuration design is considered. The principle of aperture synthesis is presented and a modified genetic optimizing algorithm is used with the fitness function being constructed. At last, Numerical results are...
In this paper, an improved interval type-2 fuzzy logic controller based on genetic algorithm is presented to deal with the problem of losing uncertain information in the type reduction process of interval type-2 fuzzy logic controller. The four uncertain boundary values of interval type-2 fuzzy output are obtained by using interval type-2 fuzzy reasoning and the Wu-Mendel uncertainty bound type reduction...
The dramatically increasing energy consumption of data centers is an important issue and one of the most efficient ways to tackle the issue is through server consolidation. The basic idea of server consolidation is to move all virtual machines (VMs) to as few energy efficient servers as possible, and then switch off unused servers. Many efficient server consolidation approaches have been proposed...
This paper presents an improved solution to optimal unit commitment (UC) by seeding best initial high fitness population (HFP) near or equal to global optimum solution to Genetic algorithm (GA). To direct the limited minimization option left in HFP in better way, easy GA mutation scheme is proposed that produces constrained satisfied populations, handle typical spinning reserve/time constraints and...
Many classification techniques can automatically summarize text into topics and accordingly identify topic terms from the online reviews. Among these techniques Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) are some of the most often employed approaches. LDA is a probability generated model that projects a document into the topic space using Dirichlet Distribution, and each...
Accurate short-term wind power prediction can improve the trade and the dispatch level of wind power. To predict the short-term wind power, we investigated the empirical mode decomposition (EMD) of numerical weather prediction (NWP) and genetic algorithm (GA) optimization of support vector regression (SVR). First, the wind speed data from NWP is decomposed into the EMD components, including multiple...
In order to improve the power supply quality of sine wave inverter for small wind power system, a control method that combines BP neural network (BPNN) with genetic algorithm (GA) is proposed in this paper. The BPNN is optimized by means of the GA to avoid the BPNN falling into local optimum value, and the optimized BPNN can better control the power output of the designed sine wave inverter. Simulation...
There are a lot of typical statistical problems in discrete combination optimization, including integer linear programming, covering problem, knapsack problem, graph theory, network flow and dispatching. As for the NPC (Non-deterministic Polynomial complete) problems, many algorithms have been developed for the discrete optimization where the heuristic algorithm is one kind of the important and effective...
Crossover methods are important keys to the success of genetic algorithms. However, traditional crossover methods fail to solve a trap problem, which is a difficult benchmark problem designed to deceive genetic algorithms to favor all-zero bits, while the actual solution is all-one bits. The Bayesian optimization algorithm (BOA) is the most famous algorithm that can solve the trap problem; however,...
Addressing the complexity and isolation of the blast furnace, field engineers generally operate the system according to their former experience. While stability and safety are the first priority, it is natural to see extra consumption of ores and fuels. Over the recent years, researchers have been searching for the optimal operation point within the blast furnace by mathematical methods that include...
In order to improve the reliability and viability, advanced aircraft is equipped with abundant multiple control surfaces. Control allocation is utilized to assign the virtual control torque to these redundant control surfaces. Due to physical and aerodynamic factors, there are some constraints impacting on each control surface, which makes the control allocation problem become more complex. In this...
Energy crisis and environmental pollution stimulate the rapid development of new energy electric vehicles. The state of charge(SOC) is a key parameter of power battery in application, so the accurate estimation is extremely important. Factors affecting the battery SOC are many and complicated, scholars have proposed many methods to estimate SOC, but still does not solve the accuracy and practicability...
The accurate identification of the helicopter flight action is the basis for guiding the training of the pilot. According to the accuracy of the helicopter flight action recognition, the paper proposed a new decision-tree-based support vector machine method to realize the helicopter multi-flight action identification. Use the tree structure of the decision tree to solve the multi-class problem of...
In recent years, logistics industry has received extensive attention with the development of online shopping. Logistics distribution is the core of logistics industry. Scientifically rational logistics distribution can save delivery cost and improve customer satisfaction. Therefore, it is very important to study the two echelon vehicle routing problem (2E-VRP) in logistics distribution.Artificial...
In the urban water supply system, the location and quantity of the pressure monitoring nodes play a significant role for the monitoring effect and the response warning of the pipe burst. However, most installation of pressure monitoring nodes are based on human experience, which cannot totally present the whole water supply system condition. In view of the unreasonable layout of pressure monitoring...
In this paper, unrelated parallel machine scheduling problem with job rejection and earliness-tardiness penalties is investigated. The objective is to minimize the total penalty cost by deciding job acceptance, assigning jobs on unrelated machines, and determining the processing sequence of jobs on each machine. To solve this problem, a mixed integer programming (MIP) model is established, and a hybrid...
Electroencefalography (EEG) has a wide range of applications in human-computer interaction and in adaptation and personalization of the interfaces. It can be used either as a sensor, e.g., for emotion detection, or as an input device that allows to take actions based on the brain's response to the presented stimuli. For the latter, it is crucial to be able to reliably detect event-related potentials...
A new long-term wind power prediction approach based on time windows is proposed to improve the accuracy and efficiency of wind power ramp prediction. An optimisation model is built to select the optimal time window size which is the key point of the wind power forecasting. First, a swinging door algorithm is applied to identify historical ramp events, and historical data is divided into several sections...
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