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Journal articles on the topic 'Optimal placement'

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Author: Grafiati

Published: 4 June 2021

Last updated: 26 January 2023

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1

K., Kiruthika. "Optimal PMU Placement Using Enhanced PSO Algorithm." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (March 31, 2020): 1877–82. http://dx.doi.org/10.5373/jardcs/v12sp4/20201674.

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2

Zhang, Hong, and Xiaohuan Wang. "Optimal Sensor Placement." SIAM Review 35, no. 4 (December 1993): 641. http://dx.doi.org/10.1137/1035141.

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3

Hsu, Chia-Ling, Rafael Matta, Sergey V. Popov, and Takeharu Sogo. "Optimal Product Placement." Review of Industrial Organization 51, no. 1 (March 22, 2017): 127–45. http://dx.doi.org/10.1007/s11151-017-9575-y.

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4

LI, YINHONG, HSIAO-DONG CHIANG, HUA LI, YUNG-TIEN CHEN, and DER-HUA HUANG. "APPLYING BIFURCATION ANALYSIS TO DETERMINE OPTIMAL PLACEMENTS OF MEASUREMENT DEVICES FOR POWER SYSTEM LOAD MODELING." International Journal of Bifurcation and Chaos 18, no. 07 (July 2008): 2111–21. http://dx.doi.org/10.1142/s0218127408021609.

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Load modeling is well known to have a significant impact on power system analysis. The task of load modeling, however, is time-consuming and expensive. Accurate load models should be developed for loads at critical locations. In this paper, applying bifurcation analysis, the problem of optimal placements of measurement devices for load model development from the viewpoint of voltage stability analysis is investigated. Voltage instability/collapse is modeled using bifurcation theory first. An optimal placement problem is formulated. An optimal placement identification scheme is proposed and applied to Taiwan power system. Optimal placements of measurement devices are identified. Validation of the selected optimal placements is performed. The robustness of optimal placements under different power transfer patterns is also examined.

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5

Rahman, Quazi, Subir Bandyopadhyay, and Yash Aneja. "Optimal regenerator placement in translucent optical networks." Optical Switching and Networking 15 (January 2015): 134–47. http://dx.doi.org/10.1016/j.osn.2014.09.002.

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6

Broad, Kevin, Andrew Mason, Mikael Ronnqvist, and Mark Frater. "Optimal Robotic Component Placement." Journal of the Operational Research Society 47, no. 11 (November 1996): 1343. http://dx.doi.org/10.2307/3010200.

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7

Broad, Kevin, Andrew Mason, Mikael Rönnqvist, and Mark Frater. "Optimal Robotic Component Placement." Journal of the Operational Research Society 47, no. 11 (November 1996): 1343–54. http://dx.doi.org/10.1057/jors.1996.170.

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8

Smirnov, Vladimir, and Bulat Kuzhin. "Optimal damper placement research." IOP Conference Series: Earth and Environmental Science 90 (October 2017): 012200. http://dx.doi.org/10.1088/1755-1315/90/1/012200.

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9

Stitz, R. W. "Optimal port site placement." Techniques in Coloproctology 14, no. 3 (August 17, 2010): 273–76. http://dx.doi.org/10.1007/s10151-010-0595-y.

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10

Lin, Jian-Fu, You-Lin Xu, and Sheng Zhan. "Experimental investigation on multi-objective multi-type sensor optimal placement for structural damage detection." Structural Health Monitoring 18, no. 3 (July 11, 2018): 882–901. http://dx.doi.org/10.1177/1475921718785182.

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An optimal sensor placement with multiple types of sensors could provide informative data of a structure to facilitate its structural damage detection. A response covariance-based multi-objective multi-type sensor optimal placement method has been thus developed. To validate this method, an experimental investigation was designed and performed in terms of a nine-bay three-dimensional frame structure, and the experimental details and results are presented in this article. The frame structure was first built, and a finite element model of the frame structure was constructed and updated. The proposed method was then applied to the finite element model to find the optimal sensor placement configuration. The multi-type sensors were then installed on the frame structure according to the determined optimal sensor numbers and positions. Different damage scenarios were then generated on the frame structure. These damage scenarios covered single and multiple damage cases occurring at different locations with different damage severities. A series of experiments, including the optimal and non-optimal sensor placements, were finally carried out, and the measurement data were used together with the finite element model to identify damage quantitatively. The identification results show that the optimal multi-type sensor placement determined by the proposed method could provide accurate damage localization and satisfactory damage quantitation and that the optimal sensor placement yielded better damage identification than the non-optimal sensor placement.

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11

CHEN, KEVIN K., and CLARENCE W. ROWLEY. "H2 optimal actuator and sensor placement in the linearised complex Ginzburg–Landau system." Journal of Fluid Mechanics 681 (June 20, 2011): 241–60. http://dx.doi.org/10.1017/jfm.2011.195.

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The linearised complex Ginzburg–Landau equation is a model for the evolution of small fluid perturbations, such as in a bluff body wake. By implementing actuators and sensors and designing an H2 optimal controller, we control a supercritical, infinite-domain formulation of this system. We seek the optimal actuator and sensor placement that minimises the H2 norm of the controlled system, from flow disturbances and sensor noise to a cost on the perturbation and input magnitudes. We formulate the gradient of the H2 squared norm with respect to the actuator and sensor placements and iterate towards the optimal placement. When stochastic flow disturbances are present everywhere in the spatial domain, it is optimal to place the actuator just upstream of the origin and the sensor just downstream. With pairs of actuators and sensors, it is optimal to place each actuator slightly upstream of each corresponding sensor, and scatter the pairs throughout the spatial domain. When disturbances are only introduced upstream, the optimal placement shifts upstream as well. Global mode and Gramian analyses fail to predict the optimal placement; they produce H2 norms about five times higher than at the true optimum. The wavemaker region is a better guess for the optimal placement.

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12

Lakdja, Fatiha, Fatima Zohra Gherbi, Redouane Berber, and Houari Boudjella. "Optimal TCSC placement for optimal power flow." Journal of Electrical Engineering 63, no. 5 (November 1, 2012): 316–21. http://dx.doi.org/10.2478/v10187-012-0046-2.

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Very few publications have been focused on the mathematical modeling of Flexible Alternating Current Transmission Systems (FACTS) -devices in optimal power flow analysis. A Thyristor Controlled Series Capacitors (TCSC) model has been proposed, and the model has been implemented in a successive QP. The mathematical models for TCSC have been established, and the Optimal Power Flow (OPF) problem with these FACTS-devices is solved by Newtons method. This article employs the Newton- based OPF-TCSC solver of MATLAB Simulator, thus it is essential to understand the development of OPF and the suitability of Newton-based algorithms for solving OPF-TCSC problem. The proposed concept was tested and validated with TCSC in twenty six-bus test system. Result shows that, when TCSC is used to relieve congestion in the system and the investment on TCSC can be recovered, with a new and original idea of integration.

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13

Mehta, Deepak, Barry O’Sullivan, Luis Quesada, Marco Ruffini, David Payne, and Linda Doyle. "Designing Resilient Long-Reach Passive Optical Networks." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 2 (August 11, 2011): 1674–80. http://dx.doi.org/10.1609/aaai.v25i2.18859.

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We report on an emerging application focused on the design of resilient long reach passive optical networks using combinatorial optimisation techniques. The objective of the application is to determine the optimal position and capacity of a set of metro nodes. We specifically consider dual parented networks whereby each customer must be associated with two metro nodes. An important property of such a placement is resilience to single node failure. Therefore excess capacity should be provided at each metro node in order to ensure that customers can be redistributed amongst the metro sites. Our application, as well as finding optimal node placements, can compute the minimum level of excess capacity on all metro nodes. In this paper we present three alternative approaches to optimal metro node placement. We present a detailed analysis of the impact of different placement approaches on the distribution of excess capacity throughout the network. We show that preferential distributions occur in practice, based on a case-study in Ireland. Finally we show that load and excess capacity provision are independent of each other.

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14

Kang, Wei, and Liang Xu. "Observability and Optimal Sensor Placement." International Journal of Sensors Wireless Communications and Controle 1, no. 2 (June 1, 2012): 93–101. http://dx.doi.org/10.2174/2210327911101020093.

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15

Kang, Wei, and Liang Xu. "Observability and Optimal Sensor Placement." International Journal of Sensors Wireless Communications and Control 1, no. 2 (July 25, 2012): 93–101. http://dx.doi.org/10.2174/2210328711101020093.

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16

Fujinaka, Toru, and Sigeru Omatu. "Pole Placement Using Optimal Regulators." IEEJ Transactions on Electronics, Information and Systems 121, no. 1 (2001): 240–45. http://dx.doi.org/10.1541/ieejeiss1987.121.1_240.

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17

Varadan, Vasundara V., Jaehwan Kim, and Vijay K. Varadan. "Optimal Placement of Piezoelectric Actuators." AIAA Journal 35, no. 3 (March 1997): 526–33. http://dx.doi.org/10.2514/2.126.

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18

Hong Zhang. "Two-dimensional optimal sensor placement." IEEE Transactions on Systems, Man, and Cybernetics 25, no. 5 (May 1995): 781–92. http://dx.doi.org/10.1109/21.376491.

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19

Spieldoch, Rachel L., Tom C. Winter, Calisa Schouweiler, Susan Ansay, Michael D. Evans, and Steven R. Lindheim. "Optimal Catheter Placement During Sonohysterography." Obstetrics & Gynecology 111, no. 1 (January 2008): 15–21. http://dx.doi.org/10.1097/01.aog.0000295865.93719.3f.

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20

Prasant Pal, Sudebkumar, Bhaskar Dasgupta, and C. E. Veni Madhavan. "Optimal polygon placement by translation1." International Journal of Computer Mathematics 52, no. 3-4 (January 1994): 139–48. http://dx.doi.org/10.1080/00207169408804299.

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21

Leung, K. H. Benjamin, Christopher L. F. Sun, Matthew Yang, Katherine S. Allan, Natalie Wong, and Timothy C. Y. Chan. "Optimal in-hospital defibrillator placement." Resuscitation 151 (June 2020): 91–98. http://dx.doi.org/10.1016/j.resuscitation.2020.03.018.

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22

Lee, Jeongwoo, Hyungsun Lim, Kyung-geun Son, and Seonghoon Ko. "Optimal Nasopharyngeal Temperature Probe Placement." Survey of Anesthesiology 59, no. 2 (April 2015): 103–4. http://dx.doi.org/10.1097/01.sa.0000460958.81813.b4.

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23

Lee, Jeongwoo, Hyungsun Lim, Kyung-geun Son, and Seonghoon Ko. "Optimal Nasopharyngeal Temperature Probe Placement." Anesthesia & Analgesia 119, no. 4 (October 2014): 875–79. http://dx.doi.org/10.1213/ane.0000000000000361.

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24

Barkalov, Sergei, Pavel Kurochka, and Tatiana Nasonova. "Optimal placement of maintenance facilities." MATEC Web of Conferences 170 (2018): 01124. http://dx.doi.org/10.1051/matecconf/201817001124.

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The article deals with the placement of service facilities and infrastructure. The most typical statements of problems are given. It is shown that the greatest difficulty is the simultaneous consideration of budget constraints and restrictions on the relative location of objects. It is shown that the application of the method of dynamic programming, in many ways can solve these problems. A heuristic algorithm for solving the problem is proposed. The issue of determining the rational number of objects intended for placement is considered. In this case, the problem reduces to determining the matching of maximum power. A heuristic algorithm is proposed that allows you to determine the required number of objects to be placed.

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25

Aksakalli, Vural, and Elvan Ceyhan. "Optimal obstacle placement with disambiguations." Annals of Applied Statistics 6, no. 4 (December 2012): 1730–74. http://dx.doi.org/10.1214/12-aoas556.

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26

Yazdi, B., P. Zanker, P. Wagner, J. Sonek, K. Pintoffl, M. Hoopmann, and K. O. Kagan. "Optimal caliper placement: manualvsautomated methods." Ultrasound in Obstetrics & Gynecology 43, no. 2 (December 22, 2013): 170–75. http://dx.doi.org/10.1002/uog.12509.

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27

Al Hasan, Mohammad, Krishna K. Ramachandran, and John E. Mitchell. "Optimal placement of stereo sensors." Optimization Letters 2, no. 1 (March 10, 2007): 99–111. http://dx.doi.org/10.1007/s11590-007-0046-5.

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28

Kim, Dongmin, Kipo Yoon, Soo Hyoung Lee, and Jung-Wook Park. "Optimal Placement and Sizing of an Energy Storage System Using a Power Sensitivity Analysis in a Practical Stand-Alone Microgrid." Electronics 10, no. 13 (July 2, 2021): 1598. http://dx.doi.org/10.3390/electronics10131598.

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The energy storage system (ESS) is developing into a very important element for the stable operation of power systems. An ESS is characterized by rapid control, free charging, and discharging. Because of these characteristics, it can efficiently respond to sudden events that affect the power system and can help to resolve congested lines caused by the excessive output of distributed generators (DGs) using renewable energy sources (RESs). In order to efficiently and economically install new ESSs in the power system, the following two factors must be considered: the optimal installation placements and the optimal sizes of ESSs. Many studies have explored the optimal installation placement and the sizing of ESSs by using analytical approaches, mathematical optimization techniques, and artificial intelligence. This paper presents an algorithm to determine the optimal installation placement and sizing of ESSs for a virtual multi-slack (VMS) operation based on a power sensitivity analysis in a stand-alone microgrid. Through the proposed algorithm, the optimal installation placement can be determined by a simple calculation based on a power sensitivity matrix, and the optimal sizing of the ESS for the determined placement can be obtained at the same time. The algorithm is verified through several case studies in a stand-alone microgrid based on practical power system data. The results of the proposed algorithm show that installing ESSs in the optimal placement could improve the voltage stability of the microgrid. The sizing of the newly installed ESS was also properly determined.

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29

Luo, Fei, Shuai Zheng, Weichao Ding, Joel Fuentes, and Yong Li. "An Edge Server Placement Method Based on Reinforcement Learning." Entropy 24, no. 3 (February 23, 2022): 317. http://dx.doi.org/10.3390/e24030317.

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In mobile edge computing systems, the edge server placement problem is mainly tackled as a multi-objective optimization problem and solved with mixed integer programming, heuristic or meta-heuristic algorithms, etc. These methods, however, have profound defect implications such as poor scalability, local optimal solutions, and parameter tuning difficulties. To overcome these defects, we propose a novel edge server placement algorithm based on deep q-network and reinforcement learning, dubbed DQN-ESPA, which can achieve optimal placements without relying on previous placement experience. In DQN-ESPA, the edge server placement problem is modeled as a Markov decision process, which is formalized with the state space, action space and reward function, and it is subsequently solved using a reinforcement learning algorithm. Experimental results using real datasets from Shanghai Telecom show that DQN-ESPA outperforms state-of-the-art algorithms such as simulated annealing placement algorithm (SAPA), Top-K placement algorithm (TKPA), K-Means placement algorithm (KMPA), and random placement algorithm (RPA). In particular, with a comprehensive consideration of access delay and workload balance, DQN-ESPA achieves up to 13.40% and 15.54% better placement performance for 100 and 300 edge servers respectively.

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30

Yamada, Shigeki, Masatsune Ishikawa, and Kazuo Yamamoto. "Utility of Preoperative Simulation for Ventricular Catheter Placement via a Parieto-Occipital Approach in Normal-Pressure Hydrocephalus." Operative Neurosurgery 16, no. 6 (August 30, 2018): 647–57. http://dx.doi.org/10.1093/ons/opy193.

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Abstract BACKGROUND Freehand ventricular catheter placement has been reported to have poor accuracy. OBJECTIVE To investigate whether preoperative computational simulation using diagnostic images improves the accuracy of ventricular catheter placement. METHODS This study included 113 consecutive patients with normal-pressure hydrocephalus (NPH), who underwent ventriculoperitoneal shunting via a parieto-occipital approach. The locations of the ventricular catheter placement in the last 48 patients with preoperative virtual simulation on the 3-dimensional workstation were compared with those in the initial 65 patients without simulation. Catheter locations were classified into 3 categories: optimal, suboptimal, and poor placements. Additionally, slip angles were measured between the ventricular catheter and optimal direction. RESULTS All patients with preoperative simulations had optimally placed ventricular catheters; the mean slip angle for this group was 2.8°. Among the 65 patients without simulations, 46 (70.8%) had optimal placement, whereas 10 (15.4%) and 9 (13.8%) had suboptimal and poor placements, respectively; the mean slip angle for the nonsimulation group was 8.6°. The slip angles for all patients in the preoperative simulation group were within 7°, whereas those for 31 (47.7%) and 10 (15.4%) patients in the nonsimulation group were within 7° and over 14°, respectively. All patients with preoperative simulations experienced improved symptoms and did not require shunt revision during the follow-up period, whereas 5 patients (7.7%) without preoperative simulations required shunt revisions for different reasons. CONCLUSION Preoperative simulation facilitates accurate placement of ventricular catheters via a parieto-occipital approach. Minimally invasive and precise shunt catheter placement is particularly desirable for elderly patients with NPH.

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31

Heydari, Ali, and Masoud-Reza Aghabozorgi. "Sensor placement for RSSD-based localization: Optimal angular placement and sequential sensor placement." Physical Communication 42 (October 2020): 101134. http://dx.doi.org/10.1016/j.phycom.2020.101134.

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32

Dens, Nathalie, Patrick De Pelsmacker, Peter Goos, and Leonids Aleksandrovs. "How to Mix Brand Placements in Television Programmes to Maximise Effectiveness." International Journal of Market Research 58, no. 5 (September 2016): 649–70. http://dx.doi.org/10.2501/ijmr-2016-022.

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This research, based on 20 brand placement campaigns for 17 brands in 11 Belgian entertainment shows, uses the mixture modelling technique to identify the optimal mix of brand placement types in a programme. It determines the ideal proportions of prop placements (branded products that are put on display during the programme, without active interaction between the product and a person), interactive placements (placements that entail interaction between a branded product and a person), and look-and-feel placements (branding elements that are visually incorporated in the scenery of the programme) to maximise brand attitude and brand recall. Controlling for programme connectedness, brand attitude is maximised when all brand placements in a programme are interactive. The optimal mix for brand recall is more diverse, and changes for consumers with different viewing frequencies. For light viewers, 39% interactive and 61% prop placements should be used. For consumers with high viewing frequency, a relatively larger proportion should be allocated to interactive placements (44%).

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33

Rostami, Minghao W., Weifan Liu, Amy Buchmann, Eva Strawbridge, and Longhua Zhao. "Optimal Design of Bacterial Carpets for Fluid Pumping." Fluids 7, no. 1 (January 5, 2022): 25. http://dx.doi.org/10.3390/fluids7010025.

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In this work, we outline a methodology for determining optimal helical flagella placement and phase shift that maximize fluid pumping through a rectangular flow meter above a simulated bacterial carpet. This method uses a Genetic Algorithm (GA) combined with a gradient-based method, the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm, to solve the optimization problem and the Method of Regularized Stokeslets (MRS) to simulate the fluid flow. This method is able to produce placements and phase shifts for small carpets and could be adapted for implementation in larger carpets and various fluid tasks. Our results show that given identical helices, optimal pumping configurations are influenced by the size of the flow meter. We also show that intuitive designs, such as uniform placement, do not always lead to a high-performance carpet.

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34

Arbesser-Rastburg, Georg, and Daniela Fuchs-Hanusch. "Serious Sensor Placement—Optimal Sensor Placement as a Serious Game." Water 12, no. 1 (December 23, 2019): 68. http://dx.doi.org/10.3390/w12010068.

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In this paper, we present a novel approach in water loss research combining two different topics: The optimal placement of pressure sensors to localize leaks in water distribution systems and Serious Gaming—games that are not only entertaining but that are also serving another purpose. The goal was to create a web interface, through which gamers could place sensors in a water distribution system model, in order to improve these sensor positions after they had been evaluated by a suitable algorithm. Two game objectives are to be pursued by the players: reaching a specified net coverage while not using more than a maximum number of sensors. For this purpose, an existing optimal sensor placement algorithm was extended and implemented, together with two hydraulic models taken from literature. The resulting Serious Game was then tested and rated in a case study. The results showed that human players are able to reach solutions that are similar regarding net coverage to those obtained by optimization, within in a short amount of time. Furthermore, it was shown that the implementation of the ideal sensor placement problem as a Serious Game motivates the players to get better and better results, while also providing them with an enjoyable gaming experience.

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35

Touya, Guillaume, and Thibaud Chassin. "RJMCMC based Text Placement to Optimize Label Placement and Quantity." Proceedings of the ICA 1 (May 16, 2018): 1–3. http://dx.doi.org/10.5194/ica-proc-1-116-2018.

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Label placement is a tedious task in map design, and its automation has long been a goal for researchers in cartography, but also in computational geometry. Methods that search for an optimal or nearly optimal solution that satisfies a set of constraints, such as label overlapping, have been proposed in the literature. Most of these methods mainly focus on finding the optimal position for a given set of labels, but rarely allow the removal of labels as part of the optimization. This paper proposes to apply an optimization technique called Reversible-Jump Markov Chain Monte Carlo that enables to easily model the removal or addition during the optimization iterations. The method, quite preliminary for now, is tested on a real dataset, and the first results are encouraging.

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36

Yi, Ting-Hua, Hong-Nan Li, and Ming Gu. "Optimal Sensor Placement for Health Monitoring of High-Rise Structure Based on Genetic Algorithm." Mathematical Problems in Engineering 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/395101.

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Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. Based on the criterion of the OSP for the modal test, an improved genetic algorithm, called “generalized genetic algorithm (GGA)”, is adopted to find the optimal placement of sensors. The dual-structure coding method instead of binary coding method is proposed to code the solution. Accordingly, the dual-structure coding-based selection scheme, crossover strategy and mutation mechanism are given in detail. The tallest building in the north of China is implemented to demonstrate the feasibility and effectiveness of the GGA. The sensor placements obtained by the GGA are compared with those by exiting genetic algorithm, which shows that the GGA can improve the convergence of the algorithm and get the better placement scheme.

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37

Haganman, Chris R., and Steven A. Aquilino. "RESTORATIVE IMPLICATIONS FOR OPTIMAL IMPLANT PLACEMENT." Oral and Maxillofacial Surgery Clinics of North America 8, no. 3 (August 1996): 387–99. http://dx.doi.org/10.1016/s1042-3699(20)30910-9.

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38

Sterling, Elizabeth K., and Doug Peterson. "Optimal Placement of Anti-Counterfeiting Indicators." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (December 2020): 1486–90. http://dx.doi.org/10.1177/1071181320641355.

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With the expansion of the internet, counterfeiting and the purchase of counterfeit goods has exploded. In spite of this, little to no research has been completed on whether or not anti-counterfeiting technologies on packages are noticed by consumers. This was an exploratory research study that examined where participants inspected product packages when specifically asked to look for authenticity cues. Participants were also asked to state what parts of the package made them feel confident in the genuineness of the product. The results found suggested that the participants in this study focused more on the words on the package. The participants did comment that they were specifically looking for spelling errors in the text. Further research is needed to continue to investigate if overt anti-counterfeit indicators are a good investment to help prevent consumers from accidentally purchasing counterfeit products.

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39

Nie, Xiaofeng, Rajan Batta, Colin Drury, and Li Lin. "Optimal Placement of Suicide Bomber Detectors." Military Operations Research 12, no. 2 (March 1, 2007): 65–78. http://dx.doi.org/10.5711/morj.12.2.65.

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40

Burns, John A., and Terry L. Herdman. "Optimal Sensor Placement for Observer Design." IFAC-PapersOnLine 54, no. 9 (2021): 446–51. http://dx.doi.org/10.1016/j.ifacol.2021.06.102.

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41

Hintermüller, Michael, Carlos N. Rautenberg, Masoumeh Mohammadi, and Martin Kanitsar. "Optimal Sensor Placement: A Robust Approach." SIAM Journal on Control and Optimization 55, no. 6 (January 2017): 3609–39. http://dx.doi.org/10.1137/16m1088867.

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42

Lee, Kwang-Hee, and Dong-Seog Han. "Optimal Sensor Placement in Multistatic Sonar." Journal of the Korea Institute of Military Science and Technology 15, no. 5 (October 5, 2012): 630–34. http://dx.doi.org/10.9766/kimst.2012.15.5.630.

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43

Freitas, Pedro. "Optimal Ball Placement in Rugby Conversions." SIAM Review 56, no. 4 (January 2014): 673–90. http://dx.doi.org/10.1137/130913225.

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44

Olague, Gustavo, and Roger Mohr. "Optimal camera placement for accurate reconstruction." Pattern Recognition 35, no. 4 (April 2002): 927–44. http://dx.doi.org/10.1016/s0031-3203(01)00076-0.

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45

Costa-Castelló, Ramon, and Luis Basañez. "Robots Optimal Placement for Cooperatively Manipulation." IFAC Proceedings Volumes 33, no. 27 (September 2000): 237–42. http://dx.doi.org/10.1016/s1474-6670(17)37935-1.

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46

Park, Young Moon, Jae Chul Kim, Young Hyun Moon, Jin Boo Choo, and Tae Won Kwon. "Optimal Meter Placement for State Estimation." IFAC Proceedings Volumes 20, no. 6 (August 1987): 379–85. http://dx.doi.org/10.1016/s1474-6670(17)59255-1.

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47

Miller, Robert E. "Optimal sensor placement via Gaussian quadrature." Applied Mathematics and Computation 97, no. 1 (December 1998): 71–97. http://dx.doi.org/10.1016/s0096-3003(97)10120-5.

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48

Minguez, Roberto, Federico Milano, Rafael Zarate-Minano, and Antonio J. Conejo. "Optimal Network Placement of SVC Devices." IEEE Transactions on Power Systems 22, no. 4 (November 2007): 1851–60. http://dx.doi.org/10.1109/tpwrs.2007.907543.

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Welton, A. "Optimal Placement of Syringe-Exchange Programs." Journal of Urban Health: Bulletin of the New York Academy of Medicine 81, no. 2 (June 1, 2004): 268–77. http://dx.doi.org/10.1093/jurban/jth113.

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Minelli, Mattia, Maode Ma, Marceau Coupechoux, Jean-Marc Kelif, Marc Sigelle, and Philippe Godlewski. "Optimal Relay Placement in Cellular Networks." IEEE Transactions on Wireless Communications 13, no. 2 (February 2014): 998–1009. http://dx.doi.org/10.1109/twc.2013.010214.130814.

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