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Articles 31 - 60 of 119
Full-Text Articles in Computer Engineering
Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation, Yunqi Xiao, Wang Yi
Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation, Yunqi Xiao, Wang Yi
Journal of System Simulation
Abstract: Due to the large number of transformers and collection lines in large-scale wind farms, the losses of collecting system is serious in actual operation. A reactive power/voltage control strategy is proposed, which takes wind turbines as the distributed reactive power sources to optimize the power flow in wind farm and reduce the overall losses of collector system. To improve the efficiency of wind farm modeling and multi-scene loss reduction simulation, a hybrid modeling and simulation scheme based on combining object model configuration and control algorithm programming is proposed. The wind farm model consists of module configuration, and can be …
Research On A Novel Biogeography-Based Optimization Algorithm Based On Ga, Wang Ning, Lisheng Wei
Research On A Novel Biogeography-Based Optimization Algorithm Based On Ga, Wang Ning, Lisheng Wei
Journal of System Simulation
Abstract: In order to further improve the optimization ability of biogeography-based optimization algorithm, a new genetic algorithm is proposed. The selection operation is added before the migration operation, and the migration individual is selected by the method of "roulette", so that the individuals with higher fitness can be preferentially migrated. The mutation operation combines the genetic gaussian mutation method, and the optimization performance of the algorithm is improved. The convergence condition of the method is derived in theory. Five test functions are used in the experiments, and the results prove that the ameliorated algorithm is better at the results of …
Simulation Of Grid-Connected Solar Micro-Inverter Based On Fuzzy Pi Controller And Feed-Forward Compensation, Weiliang Liu, Changliang Liu, Huichao Zhang, Yongjun Lin, Liangyu Ma
Simulation Of Grid-Connected Solar Micro-Inverter Based On Fuzzy Pi Controller And Feed-Forward Compensation, Weiliang Liu, Changliang Liu, Huichao Zhang, Yongjun Lin, Liangyu Ma
Journal of System Simulation
Abstract: Grid-connected solar micro-inverter is a highly nonlinear and time-varying system, so it is difficult to achieve good control effect using traditional PI controller. Small signal analysis model of micro-inverter was established, grid-connected current control strategy composed of fuzzy PI controller and grid voltage feed-forward was put forward, and the initial parameters of PI controller was optimized using the genetic algorithm. Simulation results show that the control strategy has the virtues of good robustness, small dynamic deviation, and could reduce the harmonic content of grid-connected current.
Improved Genetic Algorithm-Based Network Game Path Selection And Simulation, Jianping Gu, Mingmin Zhang, Meiliang Wang
Improved Genetic Algorithm-Based Network Game Path Selection And Simulation, Jianping Gu, Mingmin Zhang, Meiliang Wang
Journal of System Simulation
Abstract: Traditional optimal path algorithm only sets the shortest path as the target, and it does not consider the network congestion and the number of users in game area for real-time situation, thus resulting in some limitations. According to the actual circumstance of network game, network game path selection model was proposed, and the improved genetic algorithm was employed for simulation. The method pre-processed the game map to get each road weighted length value for a real-time game map, and optimization solution was obtained through the genetic algorithm. A network game path selection method based on improved genetic algorithm was …
Vehicle Routing Optimization Model Of Cold Chain Logistics Based On Stochastic Demand, Xiangguo Ma, Tongjuan Liu, Pingzhe Yang, Rongfen Jiang
Vehicle Routing Optimization Model Of Cold Chain Logistics Based On Stochastic Demand, Xiangguo Ma, Tongjuan Liu, Pingzhe Yang, Rongfen Jiang
Journal of System Simulation
Abstract: The costs of vehicle distribution in the process of cold chain logistics is analyzed and amended; A mathematical model with mixing time window is built to balance the customers' service request with importance level; To minimize the total cost, a mathematical model which uses a factor to make balance between the stability of customer demand fluctuation and the cost increase in the assignment phase is established. Based on MATLAB software, the optical solution is found with adaptive genetic algorithm by taking the background of a distribution center to simulate and analyze.
Multiresolution Scene Matching Algorithm For Infrared And Visible Images Based On Non-Subsampled Contourlet Transform, Liu Gang, Guangyu Wang, Zhou Heng, Mingjing Wang
Multiresolution Scene Matching Algorithm For Infrared And Visible Images Based On Non-Subsampled Contourlet Transform, Liu Gang, Guangyu Wang, Zhou Heng, Mingjing Wang
Journal of System Simulation
Abstract: Aiming at scene matching problem for taking infrared image as the actual data and the visible image as the referenced data, a multiresolution matching algorithm was proposed based on non-subsampled contourlet transform (NSCT). By using the transform of phase congruency transform, the difference of grayscale and contrast between infrared image and visible light image was weakened. Subsequently, the two types of images were separately transformed into non-subsampled contourlet domain and the proposed method took the Krawtchouk invariant moment as matching feature. The presented method, which used the improved genetic algorithm (GA) as searching strategy which conquered the precocious phenomenon, …
Structure Learning Of Fuzzy-Tree Based On Rigorous Binary Tree Code And Genetic Algorithm, Changliang Liu, Ziqi Wang
Structure Learning Of Fuzzy-Tree Based On Rigorous Binary Tree Code And Genetic Algorithm, Changliang Liu, Ziqi Wang
Journal of System Simulation
Abstract: To solve the problems of information redundancy and low optimization efficiency in the structure learning of fuzzy-tree model, a method based on rigorous binary tree code and genetic algorithm is proposed. The structure of fuzzy-tree model is coded by rigorous binary tree code, which improves the information redundancy of the existing matrix code. Considering the particularity of the code and the convergence of the algorithm, an improved genetic algorithm is proposed to optimize the structure of fuzzy-tree model. The experimental results show that the algorithm has good stability and computing speed on different data sets, and can find a …
3d Printing Orientation Optimization Based On Non-Dominated Sorting Genetic Algorithm, Dai Ning, Lisong Ou, Renkai Huang, Liu Hao
3d Printing Orientation Optimization Based On Non-Dominated Sorting Genetic Algorithm, Dai Ning, Lisong Ou, Renkai Huang, Liu Hao
Journal of System Simulation
Abstract: Part orientation is one of the key technologies in 3D Printing,which has important influence on the surface precision, machining time and machining cost of the part. This problem is a research hot point of how to balance the surface precision and machining time. The improved Non-dominated Sorting Genetic algorithm was proposed to solve the problem of part orientation optimization. The mathematical model of part surface accuracy and machining time were constructed. The chromosome model of part orientation and the adaptive crowding distance were established. The genetic operators of select, crossover and mutation were used to get a set of …
Boiler Combustion Optimization Based On Bayesian Neural Network And Genetic Algorithm, Haiquan Fang, Huifeng Xue, Li Ning, Fei Xi
Boiler Combustion Optimization Based On Bayesian Neural Network And Genetic Algorithm, Haiquan Fang, Huifeng Xue, Li Ning, Fei Xi
Journal of System Simulation
Abstract: Neural network and genetic algorithm have been extensively used in boiler combustion optimization problems. But the traditional Back Propagation neural network's generalization ability is poor. The Bayesian regularization can improve the neural network's generalization ability. A boiler combustion multi-objective optimization method combining Bayesian regularization BP neural network and genetic algorithm （Bayes NN-GA）was researched. A number of field test data from a boiler was used to simulate the Bayesian neural network model. The results show that the thermal efficiency and NOx emissions predicted by the Bayesian neural network model show good agreement with the measured, and the optimal results show …
Optimization Model Of Cis Network Architecture Based On Information Flow, Jianhua Li, Junwei Zhao
Optimization Model Of Cis Network Architecture Based On Information Flow, Jianhua Li, Junwei Zhao
Journal of System Simulation
Abstract: In order to explore the internal relationship between Command Information System (CIS) network and combat system, a layered combat system model was built, including organizational relationship layer, information interaction layer and communication link layer. Conception of the system coupling intensity was defined, which reflected the influence of network architecture to combat system. An optimization model of CIS network architecture aimed at maximizing the ratio of system coupling intensity to cost coefficient was built. A route programming genetic algorithm was designed and applied into simulation of Air Offensive Campaign (AOC) system network. The results show that the model and algorithm …
Cell Voltage Optimization Of Aluminum Electrolysis Based On Neural Network-Genetic Algorithm, Chenhua Xu, Li Zhi
Cell Voltage Optimization Of Aluminum Electrolysis Based On Neural Network-Genetic Algorithm, Chenhua Xu, Li Zhi
Journal of System Simulation
Abstract: In order to reduce the production cost of electrolytic aluminum, an optimization extreme method was proposed based on neural network and genetic algorithm, to find the optimal production cell voltage and the corresponding production conditions. Using kernel principal component analysis method to determine the key parameters affecting of aluminum electrolysis production, a neural network model of electrolytic aluminum was established. Using the genetic algorithm, the global optimal value of the cell voltage of the electrolytic aluminum and the corresponding production conditions were found. The simulation results show that the neural network and genetic algorithm can predict the cell …
Study On Aircraft Scheduling Optimization Based On Improved Genetic Algorithm, Yaohua Li, Wang Lei
Study On Aircraft Scheduling Optimization Based On Improved Genetic Algorithm, Yaohua Li, Wang Lei
Journal of System Simulation
Abstract: Aircraft scheduling was studied, and an optimization model of aircraft assignment based on the objective function of maximize total profit was suggested. It considered its cost and benefits by combining fleet and aircraft. In the view of the feature of this model, the innovation of genetic algorithm chromosome was carried on, and these chromosomes formatted chromosome groups. The groups interior could cross over and mutate, and the probability of crossover and mutation could dynamically adjust in accordance with adaptive values to accelerate the convergence speed, the model was resolved fast in this way. In the process of simulation with …
Integrated Dynamic Equivalent Model Of Super Capacitor Energy Storage System, Xinran Li, Tingting Xu, Shaojie Tan, Xingting Cheng, Xiaojun Zeng
Integrated Dynamic Equivalent Model Of Super Capacitor Energy Storage System, Xinran Li, Tingting Xu, Shaojie Tan, Xingting Cheng, Xiaojun Zeng
Journal of System Simulation
Abstract: As a high-power energy storage device, super capacitor (SC) is applied in micro-grid energy storage, secondary frequency regulation and peak load shifting in power system, and the research of which has become a hotspot. A second-order model of SC monomer suitable for the grid simulation was established, and the parameter identification using the charge and discharge experiment data under constant current and constant power modes was conducted based on genetic algorithm. A SC energy storage system has been set up in Simulink/Matlab based on the established second-order model of SC. The integrated dynamic equivalent model of SC energy storage …
Research On Dynamic Flexible Job Shop Scheduling Problem For Energy Consumption, Chen Chao, Wang Yan, Dahu Yan, Zhicheng Ji
Research On Dynamic Flexible Job Shop Scheduling Problem For Energy Consumption, Chen Chao, Wang Yan, Dahu Yan, Zhicheng Ji
Journal of System Simulation
Abstract: In order to solve the problem of uneven load and energy consumption under disturbance, a flexible job shop scheduling model with average flow time and energy consumption was constructed. Aiming at the above model, a genetic and simulated annealing algorithm (GASA) was designed, which is based on the genetic algorithm and the simulated annealing algorithm. A new group of individuals were generated by genetic algorithm. And then the individual simulated the annealing process, in order to avoid falling into the local optimal. Aiming at the dynamic flexible job shop scheduling problem, the rolling window technique and GASA algorithm were …
Genetic Algorithm For Solving Multi-Objective Dynamic Flexible Job Shop Scheduling, Wang Chun, Zhang Ming, Zhicheng Ji, Wang Yan
Genetic Algorithm For Solving Multi-Objective Dynamic Flexible Job Shop Scheduling, Wang Chun, Zhang Ming, Zhicheng Ji, Wang Yan
Journal of System Simulation
Abstract: To solve the scheduling problem of mold workshop in a toy factory with dynamic and flexible features, a mathematical model was established by introducing virtual operation and virtual working hours. Based on the strategies of periodic scheduling combined with dynamic event scheduling as well as the rolling window scheduling operation technology, dynamic scheduling was transformed into several continuous static scheduling windows, under which multi-objective genetic algorithm was used to solve the model. The priority of operation scheduling was given in different dynamic events. In addition, the encoding and anti-encoding of chromosome's operation sequence were made based on the proposed …
Modeling And Simulation Of Mooring Force Prediction Based On Improved Ga-Bp Network, Shifeng Li, Zhanzhi Qiu
Modeling And Simulation Of Mooring Force Prediction Based On Improved Ga-Bp Network, Shifeng Li, Zhanzhi Qiu
Journal of System Simulation
Abstract: According to the mooring security and early warning control requirement of the large open sea terminal, a ship mooring force prediction model based on genetic algorithm and BP network was studied. Environmental dynamic factors were considered and a model structure was determined by a weight statistics method; the learning method was improved by individual parent information and contemporary individual local gradient information; according to the improved model, a ship mooring force prediction method of the open sea terminal was proposed. The simulation results show that the performance of the prediction model has improved in the iteration number, …
An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi
An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi
Turkish Journal of Electrical Engineering and Computer Sciences
A genetic algorithm (GA) is not a good option for finding solutions around in neighborhoods. The current study applies a memetic algorithm (MA) with a proposed local search to the mutation operator of a genetic algorithm in order to solve the traveling salesman problem (TSP). The proposed memetic algorithm uses swap, reversion and insertion operations to make changes in the solution. In the basic GA, unlike in the real world, the relationship between generations has not been considered. This gap is resolved using the proposed complex network to allow selection among possible solutions. The degree measure has been used for …
Optimal Mission Planning Of Autonomous Mobile Agents For Applications In Microgrids, Sensor Networks, And Military Reconnaissance, Casey D. Majhor
Optimal Mission Planning Of Autonomous Mobile Agents For Applications In Microgrids, Sensor Networks, And Military Reconnaissance, Casey D. Majhor
Dissertations, Master's Theses and Master's Reports
As technology advances, the use of collaborative autonomous mobile systems for various applications will become evermore prevalent. One interesting application of these multi-agent systems is for autonomous mobile microgrids. These systems will play an increasingly important role in applications such as military special operations for mobile ad-hoc power infrastructures and for intelligence, surveillance, and reconnaissance missions. In performing these operations with these autonomous energy assets, there is a crucial need to optimize their functionality according to their specific application and mission. Challenges arise in determining mission characteristics such as how each resource should operate, when, where, and for how long. …
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale
Turkish Journal of Electrical Engineering and Computer Sciences
Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
Turkish Journal of Electrical Engineering and Computer Sciences
One of the critical factors that make a search engine fast and accurate is a concise and duplicate free index. In order to remove duplicate and near-duplicate (DND) documents from the index, a search engine needs a swift and reliable DND text document detection system. Traditional approaches to this problem, such as brute force comparisons or simple hash-based algorithms, are not suitable as they are not scalable and are not capable of detecting near-duplicate documents effectively. In this paper, a new signature-based approach to text similarity detection is introduced, which is fast, scalable, and reliable and needs less storage space. …
Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş
Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş
Turkish Journal of Electrical Engineering and Computer Sciences
Biomedical relation extraction is an important preliminary step for knowledge discovery in the biomedical domain. This paper proposes a multiple classifier system (MCS) for the extraction of chemical-induced disease relations. A genetic algorithm (GA) is employed to select classifier ensembles from a pool of base classifiers. Moreover, the voting method used for combining the members of each of the ensembles is also selected during evolution in the GA framework. The performances of the MCSs are determined by the algorithms used for selecting the classifiers, the diversity among the selected classifiers, and the voting method used in the classifier combination. The …
A Ga-Based Adaptive Mechanism For Sensorless Vector Control Of Induction Motor Drives For Urban Electric Vehicles, Asma Boulmane, Youssef Zidani, Driss Belkhayat, Marouane Bouchouirbat
A Ga-Based Adaptive Mechanism For Sensorless Vector Control Of Induction Motor Drives For Urban Electric Vehicles, Asma Boulmane, Youssef Zidani, Driss Belkhayat, Marouane Bouchouirbat
Turkish Journal of Electrical Engineering and Computer Sciences
Induction motors are more attractive to car manufacturers because they are more robust and more cost effective to maintain in comparison with other types of electric machines. The evolution of their control makes them more efficient and less expensive. However, a new control technique known as sensorless control is being used to simplify the implementation of electric machines in electric vehicles. This technique involves replacing the flux and speed sensors with an observer. The estimation of these elements is based on the measurement of currents and voltages. The main purpose of the present study is to design a novel robust …
Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose
Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose
Turkish Journal of Electrical Engineering and Computer Sciences
Cognitive Radio Sensor Network (CRSN) is known as a distributed network of wireless cognitive radio sensor nodes. Such system senses an event signal and ensures collaborative dynamic communication processes over the spectrum bands. Here, the concept of Dynamic Spectrum Access (DSA) denes the method of reaching progressively to the unused range of spectrum band. As among the essential CRSN user types, the Primary User (PU) has the license to access the spectrum band. On the other hand, the Secondary User (SU) tries to access the unused spectrum eciently, by not disturbing the PU. Considering that issue, this study introduces a …
Research On Intelligent Clustering Algorithm For Complex Water Wireless Network Surveillance, Hua Xiang, Hongtao Liang, Zhaoxin Dong, Wang Zhao, Hongjuan Yao, Baohua Li, Bingqing Jiang
Research On Intelligent Clustering Algorithm For Complex Water Wireless Network Surveillance, Hua Xiang, Hongtao Liang, Zhaoxin Dong, Wang Zhao, Hongjuan Yao, Baohua Li, Bingqing Jiang
Journal of System Simulation
Abstract: The clustering of irregular networks will cause load imbalance, which results in the phenomenon of “energy hot zone”. Aiming at the unreasonable topology of irregular network clustering, an intelligent clustering algorithm based on genetic strategy is proposed for the wireless network surveillance of complex water system. An irregular complex water topology model and an energy consumption model are built, and a genetic clustering strategy is designed via the principle of minimum energy consumption. The P matrix coding method is given, which avoids the squared increment of data calculation. Simultaneously, an adaptive genetic operator and a fuzzy modified operator are …
Path Planning For Mobile Sink Based On Enhanced Ant Colony Optimization Algorithm In Wireless Sensor Networks, Shanshan Ji
Path Planning For Mobile Sink Based On Enhanced Ant Colony Optimization Algorithm In Wireless Sensor Networks, Shanshan Ji
Journal of System Simulation
Abstract: To reduce the energy consumption and sink mobile distance of mobile sink wireless sensor networks simultaneously, a path planning algorithm for mobile sink based on enhanced ant colony optimization algorithm in wireless sensor networks is proposed. Genetic operators are introduced to ant colony optimization algorithm in order to prevent ant colony optimization premature. The non-uniform of data distribution is considered as the constraint condition, the network lifetime and sink mobile distance are considered as a multi-objective problem, and the enhanced ant colony optimization is adopted to search the Pareto sub-optimal sets of rendezvous points. The simulation results show that …
Size Optimization Method Of 6r Manipulator Based On Global Maneuverability, Xianhua Li, Xuesong Shi, Lü Lei, Leigang Zhang, Song Tao
Size Optimization Method Of 6r Manipulator Based On Global Maneuverability, Xianhua Li, Xuesong Shi, Lü Lei, Leigang Zhang, Song Tao
Journal of System Simulation
Abstract: Aiming at the six-DOF manipulator of service robot, the structure size parameters are optimized and analyzed. The global manipulability index of the manipulator workspace is defined, the coordinate system of the position and attitude is established, and the reachability of the position and attitude is calculated with the inverse solution of the manipulator, and the global manipulability index of the manipulator is proposed. Taking the maximum value of this index as the optimization target, the size parameters of the connecting rod of the manipulator are optimized by genetic algorithm, the size of the optimized connecting rod and the global …
Multi-Channel Transmission Optimization Of Campus Internet Of Things Based On Pheromone Genetic Algorithm, Zhiyong Chen, Liu Hao
Multi-Channel Transmission Optimization Of Campus Internet Of Things Based On Pheromone Genetic Algorithm, Zhiyong Chen, Liu Hao
Journal of System Simulation
Abstract: Aiming at the difficulty in selecting and optimizing the multi-path transmission of campus Internet of Things information, an optimization algorithm of network multi-path transmission based on intelligent optimization algorithm is proposed. Based on the standard genetic algorithm and the concept of pheromone concentration in ant colony algorithm, this algorithm improves the global optimization ability and convergence efficiency by controlling the evolution direction of individuals, and designs and constructs an evaluation index mathematical model which conforms to the characteristics of multi-channel information transmission optimization in the Internet of Things. The mathematical model of the evaluation index realizes the multi-channel comprehensive …
Ads-B In Based Conflict Prediction And Conflict-Free Trajectory Planning For Multi-Aircraft, Siyuan Zhang, Xianying Li, Xiaoyun Shen
Ads-B In Based Conflict Prediction And Conflict-Free Trajectory Planning For Multi-Aircraft, Siyuan Zhang, Xianying Li, Xiaoyun Shen
Journal of System Simulation
Abstract: For free flight of future, it is necessary to continuously detect conflicts and plan safe flight paths. Through in-depth analysis of detection principle of TCAS, combined with the characteristics of ADS-B data, the target within the scope of ADS-B IN surveillance is classified and given a risk factor, and the TCAS function is implemented in the ADS-B IN simulation software. For complex conflict scenarios with multi-aircraft, by meshing the conflict region and discretizing the flight procedure, the genetic algorithm is then used to calculate the optimal conflict-free trajectory based on risk factors. Two common multi-aircraft conflict scenarios are …
Multi-Objective Operation Scheduling Optimization Of Shipborne-Equipment Based On Genetic Algorithm, Jinsong Bao, Zhiqiang Li, Yaqin Zhou
Multi-Objective Operation Scheduling Optimization Of Shipborne-Equipment Based On Genetic Algorithm, Jinsong Bao, Zhiqiang Li, Yaqin Zhou
Journal of System Simulation
Abstract: Multi-objective operation scheduling of shipborne equipment is a complex combinational optimization problem under multi-task system. Existing research focuses mainly on single-objective optimization while several other objectives need to be considered during real operation such as path, duration, resource, etc. Considering the operation scheduling before exporting of an amphibious landing ship as the research object, both scheduling duration and resource requirement under the precedence constraint are optimized. The mathematical model of this multi-objective operation scheduling is established and solved using genetic algorithm. A fitness function which can be self-adaptively adjusted is designed; an adapting encoding strategy, a crossover operator, and …
Image Classification Based On Sparse Autoencoder And Support Vector Machine, Liu Fang, Lixia Lu, Hongjuan Wang, Wang Xin
Image Classification Based On Sparse Autoencoder And Support Vector Machine, Liu Fang, Lixia Lu, Hongjuan Wang, Wang Xin
Journal of System Simulation
Abstract: A new algorithm of image classification based on the sparse autoencoder and the support vector machine was proposed in view of the drawbacks that the single layer sparse autoencoder for feature learning is easy to lose the deep abstract feature and the features lack the robustness. The deep sparse autoencoder is constructed to learn each image layer and the feature of each layer is automatically extracted. The each feature weights and the reorganized set of feature are obtained according to the feature weighting method. By combining the strong global search ability of genetic algorithm and the excellent performance of …