Results 221 to 230 of about 1,097,686 (283)

Winner's Curse Free Robust Mendelian Randomization with Summary Data. [PDF]

J Am Stat Assoc
Xie Z, Zhang W, Wang J, Wu C.
europepmc   +1 more source

An enhanced connected banking system optimizer with multiple strategies for numerical optimization problems. [PDF]

Sci Rep
Yin Y, Liu H, Cai S, Ye Y.
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Hybrid ML and metaheuristic optimization of slag-fly ash-gypsum modified solidified sludge for construction. [PDF]

Sci Rep
Azarkhosh H, Chen Y, Elias S.
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IMFLKD: an incentive mechanism for decentralized federated learning based on knowledge distillation. [PDF]

Sci Rep
Ying X, Yan K, Gao X, Huang J.
europepmc   +1 more source

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Parameter analysis of negative selection algorithm

Information Sciences, 2017
Abstract The performance of negative selection algorithm (NSA) is affected by several parameters such as its self radius and expected coverage. Traditionally, most of the parameters are selected based on experience, resulting in varying performances of NSAs.
Chen Wen, Li Tao
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Revisiting Negative Selection Algorithms

Evolutionary Computation, 2007
This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to identify the fundamental characteristics of this family of algorithms and summarize their diversities.
Zhou, Ji, Dipankar, Dasgupta
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NUMERICAL NEGATIVE SELECTION ALGORITHM

International Journal on Artificial Intelligence Tools, 2010
The artificial immune algorithm is the hot topic in much research such as the intrusion detection system, the information retrieval system and the data mining system. The negative selection algorithm is the typical artificial immune algorithm. A common representation of binary strings for antibody (detector) and antigen have been associated with ...
TAO CAI, SHIGUANG JU, DEJIAO NIU
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Integrated Negative Selection Algorithm and Positive Selection Algorithm for malware detection

2016 International Conference on Progress in Informatics and Computing (PIC), 2016
Run-time malware detection strategies are efficient and robust, which get more and more attention. In this paper, we use I/O Request Package (IRP) sequences for malware detection. N-gram will be used to analyze IRP sequences for feature extraction. Integrated Negative Selection Algorithm (NSA) and Positive Selection Algorithm (PSA), through a selection
Fuyong Zhang, Ying Ma
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