Junhao Niu

Junhao Niu


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 May 2021 in PLOS ONE
Verified
Journal Article
Open access
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AZAijun Zhu
Aijun Zhu
ZGZhanqi Gu
Zhanqi Gu
CHCong Hu
Cong Hu
JNJunhao Niu
Junhao Niu
CXChuanpei Xu
Chuanpei Xu
ZLZhi Li
Zhi Li
Political optimizer (PO) is a relatively state-of-the-art meta-heuristic optimization technique for global optimization problems, as well as real-world engineering optimization, which mimics the multi-staged process of politics in human society. However, due to a greedy strategy during the election phase, and an inappropriate balance of global exploration and local exploitation during the party switching stage, it suffers from stagnation in local optima with a low convergence accuracy. To overcome such drawbacks, a sequence of novel PO variants were proposed by integrating PO with Quadratic Interpolation, Advance Quadratic Interpolation, Cubic Interpolation, Lagrange Interpolation, Newton Interpolation, and Refraction Learning (RL). The main contributions of this work are listed as follows. (1) The interpolation strategy was adopted to help the current global optima jump out of local optima. (2) Specifically, RL was integrated into PO to improve the diversity of the population. (3) To improve the ability of balancing exploration and exploitation during the party switching stage, a logistic model was proposed to maintain a good balance. To the best of our knowledge, PO combined with the interpolation strategy and RL was proposed here for the first time. The performance of the best PO variant was evaluated by 19 widely used benchmark functions and 30 test functions from the IEEE CEC 2014. Experimental results revealed the superior performance of the proposed algorithm in terms of exploration capacity.

16 February 2023 in Photonics
Verified
Journal Article
Open access
PDF file
AZAijun Zhu
Aijun Zhu
PBPengcheng Bu
Pengcheng Bu
CHCong Hu
Cong Hu
JNJunhao Niu
Junhao Niu
RMRabi N. Mahapatra
Rabi N. Mahapatra
In this paper, a plasmonic electro-optical encoder based on graphene at THz frequency is proposed. The surface plasmon polaritons (SPPs) in the graphene–insulator–metal structure are excited by an incident TM wave with a wavelength of 9.3 μm. Graphene plasma waveguides have extremely high confinement, relatively low losses, and high tunability. The switching mechanism is based on the application of an external voltage to locally change the chemical potential of the graphene for encoding. Setting the chemical potential to 1 eV allows SPPs to propagate while lowering the chemical potential to 0.1 eV prevents the SPPs from propagating. A 4 × 2 encoder with a minimum encoding extinction ratio (ER) of 37 dB, a maximum modulation depth (MD) of 99.99%, and a structure area of 0.8 μm2 is proposed based on the design rules and simulations using the finite-difference time-domain (FDTD) method. In terms of the obtained results, the proposed structure can be used in optical integrated circuits.