Numerical circuit parameter extraction (PE) is a key sub-process of space mapping (SM), which is used to efficiently optimize full-wave EM responses of microwave structures exploiting faster but inaccurate physics-bas...
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ISBN:
(数字)9798331540401
ISBN:
(纸本)9798331540418
Numerical circuit parameter extraction (PE) is a key sub-process of space mapping (SM), which is used to efficiently optimize full-wave EM responses of microwave structures exploiting faster but inaccurate physics-based auxiliary models. Any improvement in PE has a positive impact on SM design optimization. In this paper, we apply for the first time a PE formulation based on the Kullback-Leibler distance to microstrip filters using their full-wave EM responses as targets. We perform a rigorous numerical comparison of PE based on the K-L formulation against PE using classical norms. Our results confirm a better PE performance using the Kullback-Leibler formulation than those obtained with traditional PE formulations.
Cardinality estimation is the problem of estimating the size of the output of a query, without actually evaluating the query. The cardinality estimator is a critical piece of a query optimizer, and is often the main c...
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This paper explores the optimization of a rural bus and heterogeneous drone collaborative delivery system, aiming to reduce operational costs while enhancing delivery efficiency. A two-phase optimization approach is p...
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ISBN:
(数字)9798331536169
ISBN:
(纸本)9798331536176
This paper explores the optimization of a rural bus and heterogeneous drone collaborative delivery system, aiming to reduce operational costs while enhancing delivery efficiency. A two-phase optimization approach is proposed, starting with the K-means clustering algorithm to partition demand points around bus stations, ensuring that each cluster has a designated drone launch point. In the first phase, a linear programming model is used to determine the delivery routes and schedules for Type A drones, minimizing delivery costs. The second phase expands the model to include three types of heterogeneous drones, with each drone type selected based on its payload capacity and flight characteristics. A simulated annealing algorithm is employed to optimize the drone deployment and delivery paths, further minimizing costs. The system also incorporates revenue optimization by considering pickup operations, where income is generated from collecting goods along the delivery route. The final model significantly improves the economic and operational efficiency of the rural delivery system, providing a practical solution for rural logistics and offering insights applicable to other collaborative delivery scenarios.
A variant of the well-known Set Covering Problem is studied in this paper, where subsets of a collection have to be selected, and pairwise conflicts among subsets of items exist. The selection of each subset has a cos...
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Efficient and reliable resource allocation algorithm is one of the key problems for the realization of cognitive radio networks. Due to the rapidly changing characteristics of cognitive environment, water-filling algo...
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Efficient and reliable resource allocation algorithm is one of the key problems for the realization of cognitive radio networks. Due to the rapidly changing characteristics of cognitive environment, water-filling algorithm is difficult to meet this environment because of the interaction with primary users. In this paper, we propose a primary user Quality of service (QoS) and activity concerned resource allocation algorithm in OFDM based cognitive radio system with a risk-return model which reflects availability of subcarriers or primary user activity and date transmission outage probability constraint to guarantee primary users' QoS. Taking maximization of the expected sum rate of cognitive system as the objective function, we solve this optimization problem by a Lagrangian dual method under the introduced primary user outage probability constraint. Finally, the performance comparison of water-filling algorithm and our algorithm is given. The simulation results show that the proposed algorithm can obtain more transmission capacity and effectively guarantee primary users' QoS.
Energy minimization is one of the significant tasks in the WSN which can be achieved through clustering process. Clustering in the WSN is an efficient method to increase the lifespan of the network. In the proposed wo...
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Energy minimization is one of the significant tasks in the WSN which can be achieved through clustering process. Clustering in the WSN is an efficient method to increase the lifespan of the network. In the proposed work the main concentration is given to the network lifetime which is very necessary for the less node failures and high packet deliveries. In this paper the hierarchical structuring is done using clustering approach based on efficient data aggregation process. The aggregation process is defined into two phases. The first phase defines the arrangement of the nodes in the cluster using uniform distribution and second phase defines the selection of the cluster head and aggregation of the data using linear programming. The main objective is to minimize the energy consumption and increase of the robustness of the sensor network. Eventually the performance of the network will be evaluated in terms of low energy consumption, high packet deliveries and low congestions in the WSN.
Optimal placement problems of electrical devices in power systems have attracted greater attention from researchers in literature. Therefore, in the last 60 years, a wide range of solutions and methodologies have been...
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Optimal placement problems of electrical devices in power systems have attracted greater attention from researchers in literature. Therefore, in the last 60 years, a wide range of solutions and methodologies have been developed for optimally allocated shunt capacitors, generation sources, switches, transformers, and many other electrical devices in transmission, distribution, and microgrid systems. This large number of methods are paramount to place any electric device with the ability to influence any network parameter. However, this article concentrates on how these works have wrongly impacted the efficiency of the methods developed for the allocation of renewable distributed generation in public distribution networks. To track down this negative impact, a historical literature review of the optimal placement efforts of electric devices in power systems is proposed. Additionally, the existing research works are reviewed from the perspective of their considered device types, design variables, network type, and objective function. Three cumulated shortcomings are identified and discussed. The main aim of this article is to bridge the gap between the efforts developed in the literature and their implementation with renewable generation units and public distribution networks, and also to reorient future works to develop concrete methodologies able to bring benefits for all distribution market actors.
In recent years, non-negative matrix factorization (NMF) cluster analysis of multi-view data has shown outstanding results in data mining and machine learning. Multi-view data typically encompasses complementary eleme...
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ISBN:
(数字)9798331519582
ISBN:
(纸本)9798331519599
In recent years, non-negative matrix factorization (NMF) cluster analysis of multi-view data has shown outstanding results in data mining and machine learning. Multi-view data typically encompasses complementary elements from multiple perspectives. Finding a consensus solution that works for all the different views is a difficult task. This study proposes a novel NMF-based clustering method that utilizes various manifold regularizations for multi-view data to address the previously mentioned problem. In this method, the NMF will decompose the input data into the two non-negative matrices. Next, we employ the manifold scenario to preserve the geometric structure within the data. Lastly, we design the novel objective function by combining all the earlier mentioned terms and then optimize it using the iterative strategy method to achieve the optimal solution. The empirical analysis of real-world datasets indicates that the proposed method outperforms numerous existing techniques in clustering efficiency.
Path planning and optimization play an important role in robotics and autonomous vehicles. In this work we address the particular problem of optimizing sets of non-overlapping paths which form lanes for the efficient ...
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ISBN:
(数字)9798331509293
ISBN:
(纸本)9798331509309
Path planning and optimization play an important role in robotics and autonomous vehicles. In this work we address the particular problem of optimizing sets of non-overlapping paths which form lanes for the efficient flow of multiple agents in a given cluttered environment. The proposed method is based on a convex optimization formulation applied to a piecewise Quadratic Bezier path representation. Our method guarantees a given minimum clearance value while minimizing total length and maximum curvature. Clearance is addressed with respect to both obstacles and adjacent lanes, such that a non-overlapping set of lanes is obtained. The proposed method is based on interleaving the optimization of individual lanes according to a priority criterion that improves overall convergence. Users have the flexibility to customize the objective function by assigning different weights to the clearance, length, and curvature objective terms. We present results applied to sets of lanes generated by an RRT planner which has been extended to produce multiple initial lanes. Our results showcase the ability to produce different sets of lanes reflecting user-defined weights. We also present comparisons against a heuristic shortcut-based smoothing method and a generalized optimization formulation, which demonstrate the improved performance of the proposed approach.
In this paper, we propose a global monotonicity consistency training strategy for quality assessment, which includes a differentiable, low-computation monotonicity evaluation loss function and a global perception trai...
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