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As various types of Internets of Things (IoT) are deployed in a wide range of areas, the need arises to utilize various IoT resources dynamically to accomplish user tasks. We call this environment an urban-scale IoT environment, where various IoT resources that are necessary to accomplish user tasks are directly connected to each other via users' mobile devices, such as their smart phones. IoT resources...
A novel solution to the problem of integrated exploration of datapath resource configuration and loop unrolling factor (UF) for control data flow graphs (CDFGs) during high level synthesis (HLS) for optimal scheduling is presented in this paper. The proposed approach is fast as it is driven through an adaptive genetic algorithm (GA) process, capable of escaping local minima and an estimation model...
Genetic algorithm (GA) has been widely used in a variety of communication network design problems. The encoding method is the essential issue for GA. In this paper we investigate the topology optimization of the tree-like overlay multicast systems with degree constraints. A new encoding method based on the degree-weighted array is proposed. It requires no repair strategies for the encoding, crossover...
Genetic Algorithm and Association Rules both are commonly used methods in data mining. In this paper, a brief overview of Genetic Algorithm and Association Rules has been given, and this paper has presented an improved extract method of association rules of genetic algorithm based on their respective advantages and disadvantages. It also did some research on designing encoding methods, structuring...
In order to solve the problems such as blindfold search, slower convergence, and sometimes unsuccessfully search in the present genetic algorithms used for intelligent test paper generation, this paper introduces an improved genetic algorithm for intelligent test paper generation. This algorithm generates optimized initial chromosome group and controlling crossing and variation recurring to test paper...
On the basis of multiple transport mode selection, the paper presents the route optimization model for single-task from one origination to several destinations in the fourth party logistics, and gives the solution of Genetic Algorithms. In the algorithms, a length-variant encoding scheme of round number is adopted to represent the selected route, and idea that keeps the best individual is used. The...
This article introduced the traditional genetic algorithm and quantum genetic algorithm at first. On the basis of the two algorithms, an improved genetic algorithm is proposed to handle array beam forming optimization problems. The results of simulation show that the improved genetic algorithm is effective and satisfactory in resolving the problem of beam forming of adaptive array of smart antennas.
In this paper we address the resolution of the Ground Station Scheduling problem by Genetic Algorithms. Ground Stations (GS) are required during spacecraft (S/C) operations to provide communications links between operations teams and the S/C systems. Basic communication types, such as telemetry, tele-command and tracking, are all supported by the same satellite and GS systems. The allocation of ground...
Personalized learning is one of the main problems associated with the online remedial education (ORE) for e_learning systems. The current composition approaches fail to take into consideration the difference in individual learning-competency and the background knowledge of the individual learners and thus don't provide the adequate teaching sequence that exactly meets the demands of the individual...
A neural representation of combinational logic circuit is proposed, called `Logical Neural Network' (LNN). LNN is a feed-forward neural network (NN) where the weights of the network indicate the connections of digital circuit. The logic operations of the circuit such as AND, OR, NOR etc are performed with the neurons of LNN. A modification of Simple Genetic Algorithm (mSGA) is applied to design and...
An embedded system, based on the field programmable gate array (FPGA) technology is proposed for mitigation of a flawed-array radiation. The current solution includes a genetic algorithm (GA) that finds a new set of the array excitation parameters in case the radiation pattern of the flawed array is unacceptably degraded with respect to the originally designed pattern. A successful real-time mitigation...
Interactive interpolating crossover allows a user to quickly see a large number of individuals formed by interactively-controlled interpolation between two or more parents. We study it here for the first time in the context of grammatical evolution (GE). We define methods of quantifying the behaviour of interpolations and use them to compare two methods of performing interpolation and two encodings...
Storage subsystem performance has been a bottleneck of improving computer system performance. In order to minimize the disk response time for every file access request, choosing a near-optimal striping unit is one good way. In this paper, we present a new scheme based on Disk Striping and Genetic Algorithms to choose the striping unit. We establish the relationship between the disk response time and...
Paper describes a hybrid genetic algorithm (HGA) developed as a combination of a binary genetic and steepest descent gradient (SDG) algorithms. Here genetic algorithm (GA) performs global exploration of the whole design space aiming at identification of a given number of promising solutions, whereas SDG algorithm is used to refine these nearly optimal solutions via local down-hill optimization. Such...
It has been proven recently that using Mobile Agent (MA) in wireless sensor networks (WSNs) can drastically help to obtain the flexibility of application-aware deployment. Normally, in any MA based sensor network, it is an important research issue to find out an optimal itinerary for the MA in order to achieve efficient and effective data collection from multiple sensory data source nodes. In this...
Genetic algorithm is an important algorithm of association rule mining. However, there is some issues that genetic algorithm easy to lead prematuring convergence and into the plight of local optimum, or convergence too much time and consume a large amount of time to search. For resolving this issues, the paper improves the algorithm through adopting an adaptive mutation rate and improving the methods...
A transmitting beam shaping scheme with limited amplitude weighted values for satellite active phased array antenna is presented to meet lower sidelobe and higher power amplifiers efficiency. The scheme is implemented by a dual coding genetic algorithm (GA) .Phase and amplitude of array weight vectors for shaped beam are encoded by real coding and finite length binary coding, which, maintaining accuracy...
This paper proposes a new strategy for solving the service restoration problem in large-scale distribution systems (DS). Due to the presence of various conflicting objective functions and constraints, the service restoration task is a multi-objective, multi-constraint optimization problem. As a consequence, finding feasible solutions is a hard task. The proposed strategy uses a new tree encoding,...
An improved gene expression programming (IGEP) is proposed in this paper. It has some new features: 1) introducing a new individual coding; 2) introducing a new way of creating constants; 3) introducing a hybrid self-adaptive crossover-mutation operator, which can enhance the search ability and exploit the optimum offspring. To validate the performance of IGEP, this paper applies IGEP into the solution...
This research was aimed to present the methodology of genetic algorithm for exam proctor schedules used in educational institutes. The purpose of the study is to cut down time for organizing each staffs proctoring table. Every staff has equal of proctoring during normal and extra workload. It is also able to avoid exam proctoring on weekend and on the staff engaged duration. In the experiment, the...
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