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A novel modified binary differential evolution algorithm and its applications
Differential Evolution (DE) is a simple yet efficient global optimization algorithm. However, the standard DE and most of its variants operate in the continuous space, which cannot solve theExpand
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A Modified Binary Differential Evolution Algorithm
Differential evolution (DE) is a simple, yet efficient global optimization algorithm. As the standard DE and most of its variants operate in the continuous space, this paper presents a modifiedExpand
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NOKMeans: Non-Orthogonal K-means Hashing
Finding nearest neighbor points in a large scale high dimensional data set is of wide interest in computer vision. One popular and efficient approach is to encode each data point as a binary code inExpand
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A Novel Hybrid Binary PSO Algorithm
The continuous PSO algorithm has been widely researched and also applied as an intelligent computational technique to solve problems requiring iterative solutions based on some predefined objectiveExpand
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Optimal node placement in industrial Wireless Sensor Networks using adaptive mutation probability binary Particle Swarm Optimization algorithm
Industrial Wireless Sensor Networks (IWSNs), a novel technique in the field of industrial control, can greatly reduce the cost of measurement and control, as well as improve productive efficiency.Expand
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Deep Learning-Based Intrusion Detection for IoT Networks
Internet of Things (IoT) has an immense potential for a plethora of applications ranging from healthcare automation to defence networks and the power grid. The security of an IoT network isExpand
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Optimal node placement of industrial wireless sensor networks based on adaptive mutation probability binary particle swarm optimization algorithm
Industrial Wireless Sensor Networks (IWSNs), a novel technique in industry control, can greatly reduce the cost of measurement and control and improve productive efficiency. Different fromExpand
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A Modified Multi-objective Binary Particle Swarm Optimization Algorithm
In recent years a number of works have been done to extend Particle Swarm Optimization (PSO) to solve multi-objective optimization problems, but a few of them can be used to tackle binary-codedExpand
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Auto-JacoBin: Auto-encoder Jacobian Binary Hashing
Binary codes can be used to speed up nearest neighbor search tasks in large scale data sets as they are efficient for both storage and retrieval. In this paper, we propose a robust auto-encoder modelExpand
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Improved Spectral Clustering Using Adaptive Mahalanobis Distance
In this paper, we consider the manifold clustering problem. In manifold clustering, data are sampled from multiple manifolds and the goal is to partition the data accordingly. Spectral clusteringExpand
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