Purpose/significance Panoramic backtracking integrates the thinking mode of panoramic analysis with the traditional methods of text analysis and document metrology and visualization technology, to ...achieve the expansion and innovation of the review research framework. Method/process Based on the analysis of concepts and basic attributes of panoramic backtracking, this paper constructed a new framework of five processes including data collection and delamination, diagnosis of time slices, analysis of dimensional model structure, hierarchical recursive visual situation presentation, and combined overall conclusion acquisition. The paper took the research on the performance appraisal of financial expenditure in China as an example for exploratory verification. Result/conclusion This paper proves that panoramic backtracking has comparative advantages in terms of diversification of data collection, refinement of the analysis process, standardization of the process design, and more comprehensive conclusion.
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•A recently BSOA-based approach is applied to allocate multi-type DGs.•The BSOA needs very little effort in tuning control parameters.•Fuzzy expert rules to indicate bus suitability ...for DG’s placement are defined.•An effort to tackle the shortfall of LSFs is attempted.•Considerable reductions in power losses and voltage deviations are realized.
In this article, a very recently swarm optimization technique namely a backtracking search optimization algorithm (BSOA) is addressed to assign the distributed generators (DGs) along radial distribution networks. One of the main features of the BSOA is a single control parameter and not over sensitive to the initial value of this factor. The objective function is adapted with weighting factor to reduce the network real loss and enhance the voltage profile with the purpose of improving the operating performance. In addition, the combined power factor and reduction in network reactive power loss are spotted. Set of fuzzy expert rules using loss sensitivity factors and bus voltages are employed to identify the initial DG’s locations. The proposed approach is attuned to tackle the shortfall of loss sensitivity factors and to decide the final placement of the DGs. Two types of the DGs are studied and investigated. The proposed method is demonstrated and validated thru many radial distribution networks with different sizes and complexities. The BSOA-based methodology can efficiently generate high-quality solutions compared to other competitive techniques in the literature.
•MLBSA is proposed to identify the parameters of PV models.•Multiple learning strategy aims to balance exploration and exploitation abilities.•Elite method based on chaotic local search is used to ...refine population quality.•Comprehensive experimental results indicate the competitive performance of MLBSA.
Obtaining appropriate parameters of photovoltaic models based on measured current-voltage data is crucial for the evaluation, control, and optimization of photovoltaic systems. Although many techniques have been developed to solve this problem, it is still challenging to identify the model parameters accurately and reliably. To improve parameters identification of different photovoltaic models, a multiple learning backtracking search algorithm (MLBSA) is proposed in this paper. In MLBSA, some individuals learn from the current population information and historical population information simultaneously, which aims to maintain population diversity and enhance the exploration ability. While other individuals learn from the best individual of current population to improve the convergence speed and thus enhance the exploitation ability. In addition, an elite strategy based on chaotic local search is developed to further refine the quality of current population. The proposed MLBSA is employed to solve the parameters identification problems of different photovoltaic models, i.e., single diode, double diode, and photovoltaic module. Comprehensive experimental results and analyses demonstrate that MLBSA outperforms other state-of-the-art algorithms in terms of accuracy, reliability, and computational efficiency.
We prove new properties of the non-backtracking graph and the non-backtracking Laplacian for graphs. In particular, among other results, we prove that two simple graphs are isomorphic if and only if ...their corresponding non-backtracking graphs are isomorphic, and we investigate properties of various classes of non-backtracking Laplacian eigenfunctions, such as symmetric and antisymmetric eigenfunctions. Moreover, we introduce and study circularly partite graphs as a generalization of bipartite graphs, and we use this notion to state a sharp upper bound for the spectral gap from 1. We also investigate the singular values of the non-backtracking Laplacian in relation to independence numbers, and we use them to bound the moduli of the eigenvalues.
We introduce a non-backtracking Laplace operator for graphs and we investigate its spectral properties. With the use of both theoretical and computational techniques, we show that the spectrum of ...this operator captures several structural properties of the graph in a more precise way than the classical operators that have been studied so far in the literature, including the non-backtracking matrix.
Summary
Mobility prediction and fault tolerance are extremely difficult due to underwater characteristics. Energy drain is one of the major causes for node faults. Hence, in this research article, a ...hybrid optimization algorithm is developed for fault‐tolerant and accurate localization in UWSN. In this technique, Artificial Butterfly Optimization (ABO) algorithm is applied for finding the distance between the anchors and the sensors. Each non‐localized node runs ABO algorithm for finding the distance amid the anchor or beacon nodes. Then, applying Quaternion‐based Backtracking Search Optimization (QBSA) algorithm, non‐localized sensor nodes are localized and to decrease the localization error based on the Received Signal Strength Indicator (RSSI), battery energy, and distance parameters. Aqua‐Sim a tool kit of NS2 is an open‐source software developed for Underwater Wireless Sensor Network research, and this proposed algorithm will be implemented using this software. By simulation results, it is shown that the proposed optimization algorithm reduces the localization error, latency, and cost and energy consumption.
In water, sensor nodes are not fixed and are mobile in nature due to water currents or tectonic plate's movements. So the mobility of sensor nodes is considered in the proposed scheme as it's tough to calculate the exact difference among sensor nodes.
In this technique, for accurate localization of mobile nodes with reduced latency, a range‐based localization technique is optimized, and a hybrid optimized localization technique is developed.
Using drones to carry out commercial parcel delivery can significantly promote the transformation and upgrading of the logistics industry thanks to the saving of human labor source, which is becoming ...a new component of intelligent transportation systems. However, the flight distance of drones is often constrained due to the limited battery capacity. To address this challenge, this paper designs a multi-drones-assisted commercial parcel delivery system, which supports long-distance delivery by a generalized service network (GSN). Each node of the GSN is equipped with charging piles to provide a charging service for drones. Given the limited number of charging piles at each node and the limited battery capacity of a drone, to ensure the efficient operation of the system, the flight planning problem of drones is converted into a large-scale optimization problem by a priority-based encoding mechanism. To solve this problem, an enhanced backtracking search algorithm (EBSA) is reported, which is inspired by the characteristics of the considered flight planning problem and the weak ability of the backtracking search algorithm to escape from a local optimum. The core components of EBSA are the designed comprehensive learning mechanism and local escape operator. Experimental results prove the validity of the improved strategies and the excellent performance of EBSA on the considered flight planning problem.
•A new measure of centrality by modifying classic PageRank and Hashimoto matrix.•Higher order random walkers with memory are considered.•Line graph associated to a directed network and the Hashimoto ...matrix are used.•Several applications to public transportation systems are included.
Non-backtracking centrality was introduced as a way to correct what may be understood as a deficiency in the eigenvector centrality, since the eigenvector centrality in a network can be artificially increased in high-degree nodes (hubs) because a hub is central because its neighbors are central, but these, in turn, are central just because they are hub neighbors. We define the non-backtracking PageRank as a new measure modifying the well-known classic PageRank in order to avoid the possibility of the random walker returning to the node immediately visited (non-backtracking walk). But, as we show, this measure presents a gap and a remarkable difference between the limit of “no penalty for return trips” and the direct calculation of the non-backtracking PageRank. Also, as it is shown in the applications presented, in certain cases this new measure produces notable variations with respect to the classifications obtained by the classic PageRank.
Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation in wireless networks and offers a great variety of possible performance and ...implementation gains. Motivated by this, we study the achievable rate optimization for multi-stream multiple-input multiple-output (MIMO) systems equipped with an RIS, and formulate a joint optimization problem of the covariance matrix of the transmitted signal and the RIS elements. To solve this problem, we propose an iterative optimization algorithm that is based on the projected gradient method (PGM). We derive the step size that guarantees the convergence of the proposed algorithm and we define a backtracking line search to improve its convergence rate. Furthermore, we introduce the total free space path loss (FSPL) ratio of the indirect and direct links as a first-order measure of the applicability of RISs in the considered communication system. Simulation results show that the proposed PGM achieves the same achievable rate as a state-of-the-art benchmark scheme, but with a significantly lower computational complexity. In addition, we demonstrate that the RIS application is particularly suitable to increase the achievable rate in indoor environments, as even a small number of RIS elements can provide a substantial achievable rate gain.
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