An ant colony optimization method for generalized TSP problem

Focused on a variation of the euclidean traveling salesman problem (TSP), namely, the generalized traveling salesman problem (GTSP), this paper extends the ant colony optimization method from TSP to this field. By considering the group influence, an improved method is further improved. To avoid locking into local minima, a mutation process and a local searching technique are also introduced into this method. Numerical results show that the proposed method can deal with the GTSP problems fairly well, and the developed mutation process and local search technique are effective

Multilayer perceptron network optimization for chaotic time series modeling

Chaotic time series are widely present in practice, but due to their characteristics—such as internal randomness, nonlinearity, and long-term unpredictability—it is difficult to achieve high-precision intermediate or long-term predictions. Multi-layer perceptron (MLP) networks are an effective tool for chaotic time series modeling. Focusing on chaotic time series modeling, this paper presents a generalized degree of freedom approximation method of MLP. We then obtain its Akachi information criterion, which is designed as the loss function for training, hence developing an overall framework for chaotic time series analysis, including phase space reconstruction, model training, and model selection. To verify the effectiveness of the proposed method, it is applied to two artificial chaotic time series and two real-world chaotic time series. The numerical results show that the proposed optimized method is effective to obtain the best model from a group of candidates. Moreover, the optimized models perform very well in multi-step prediction tasks.This research was funded in part by the NSFC grant numbers 61972174 and 62272192, the Science-Technology Development Plan Project of Jilin Province grant number 20210201080GX, the Jilin Province Development and Reform Commission grant number 2021C044-1, the Guangdong Universities’ Innovation Team grant number 2021KCXTD015, and Key Disciplines Projects grant number 2021ZDJS138

Combining Battery‐Type and Pseudocapacitive Charge Storage in Ag/Ti3C2Tx MXene Electrode for Capturing Chloride Ions with High Capacitance and Fast Ion Transport

The recent advances in chloride‐ion capturing electrodes for capacitive deionization (CDI) are limited by the capacity, rate, and stability of desalination. This work introduces Ti3C2Tx/Ag synthesized via a facile oxidation‐reduction method and then uses it as an anode for chloride‐ion capture in CDI. Silver nanoparticles are formed successfully and uniformly distributed with the layered‐structure of Ti3C2Tx. All Ti3C2Tx/Ag samples are hydrophilic, which is beneficial for water desalination. Ti3C2Tx/Ag samples with a low charge transfer resistance exhibit both pseudocapacitive and battery behaviors. Herein, the Ti3C2Tx/Ag electrode with a reaction time of 3 h exhibits excellent desalination performance with a capacity of 135 mg Cl− g−1 at 20 mA g−1 in a 10 × 10−3 m NaCl solution. Furthermore, low energy consumption of 0.42 kWh kg−1 Cl− and a desalination rate of 1.5 mg Cl− g−1 min−1 at 50 mA g−1 is achieved. The Ti3C2Tx/Ag system exhibits fast rate capability, high desalination capacity, low energy consumption, and excellent cyclability, which can be ascribed to the synergistic effect between the battery and pseudocapacitive behaviors of the Ti3C2Tx/Ag hybrid material. This work provides fundamental insight into the coupling of battery and pseudocapacitive behaviors during Cl− capture for electrochemical desalination

In-fill asymptotic theory for structural break point in autoregression: A unified theory

Published in Econometric Reviews, 2020 July. https://doi.org/10.1080/07474938.2020.1788822</p

New distribution theory for the estimation of structural break point in mean

Ministry of Education, Singapore under its Academic Research Funding Tier