scholarly journals Optimal Control of Probabilistic Logic Networks and Its Application to Real-Time Pricing of Electricity

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Koichi Kobayashi ◽  
Kunihiko Hiraishi
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Discrete Model ◽  
Large Scale ◽  
Mixed Integer ◽  
Probabilistic Logic ◽  
Integer Linear Programming Problem ◽  
Real Time Pricing ◽  
Electricity Conservation ◽  
Logic Functions

In analysis and control of large-scale complex systems, a discrete model plays an important role. In this paper, a probabilistic logic network (PLN) is considered as a discrete model. A PLN is a mathematical model where multivalued logic functions are randomly switched. For a PLN with two kinds of control inputs, the optimal control problem is formulated, and an approximate solution method for this problem is proposed. In the proposed method, using a matrix-based representation for a PLN, this problem is approximated by a mixed integer linear programming problem. In application, real-time pricing of electricity is studied. In real-time pricing, electricity conservation is achieved by setting a high electricity price. A numerical example is presented to show the effectiveness of the proposed method.

scholarly journals Distributed Real-Time Pricing Control for Large-Scale Unidirectional V2G With Multiple Energy Suppliers

2016 ◽  
Vol 12 (5) ◽  
pp. 1953-1962 ◽  
Author(s):  
Navid Rahbari-Asr ◽  
Mo-Yuen Chow ◽  
Jiming Chen ◽  
Ruilong Deng
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Real Time Pricing ◽  
Pricing Control

scholarly journals A Probabilistic Approach to Control of Complex Systems and Its Application to Real-Time Pricing

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Koichi Kobayashi ◽  
Kunihiko Hiraishi
Keyword(s):  
Complex Systems ◽  
Real Time ◽  
Structural Control ◽  
Regulatory Networks ◽  
Control Method ◽  
Probabilistic Approach ◽  
Gene Regulatory ◽  
Real Time Pricing ◽  
Electricity Conservation ◽  
Approximate Solution Method

Control of complex systems is one of the fundamental problems in control theory. In this paper, a control method for complex systems modeled by a probabilistic Boolean network (PBN) is studied. A PBN is widely used as a model of complex systems such as gene regulatory networks. For a PBN, the structural control problem is newly formulated. In this problem, a discrete probability distribution appeared in a PBN is controlled by the continuous-valued input. For this problem, an approximate solution method using a matrix-based representation for a PBN is proposed. Then, the problem is approximated by a linear programming problem. Furthermore, the proposed method is applied to design of real-time pricing systems of electricity. Electricity conservation is achieved by appropriately determining the electricity price over time. The effectiveness of the proposed method is presented by a numerical example on real-time pricing systems.

scholarly journals Reconciling periodic rhythms of large-scale biological networks by optimal control

2020 ◽  
Vol 7 (1) ◽  
pp. 191698 ◽  
Author(s):  
Meichen Yuan ◽  
Junlin Qu ◽  
Weirong Hong ◽  
Pu Li
Keyword(s):  
Optimal Control ◽  
Biological Networks ◽  
Large Scale ◽  
State Transition ◽  
Control Strategies ◽  
Underlying Mechanism ◽  
Mixed Integer ◽  
Optimal Control Strategy ◽  
Living Organisms ◽  
External Signals

Periodic rhythms are ubiquitous phenomena that illuminate the underlying mechanism of cyclic activities in biological systems, which can be represented by cyclic attractors of the related biological network. Disorders of periodic rhythms are detrimental to the natural behaviours of living organisms. Previous studies have shown that the state transition from one to another attractor can be accomplished by regulating external signals. However, most of these studies until now have mainly focused on point attractors while ignoring cyclic ones. The aim of this study is to investigate an approach for reconciling abnormal periodic rhythms, such as diminished circadian amplitude and phase delay, to the regular rhythms of complex biological networks. For this purpose, we formulate and solve a mixed-integer nonlinear dynamic optimization problem simultaneously to identify regulation variables and to determine optimal control strategies for state transition and adjustment of periodic rhythms. Numerical experiments are implemented in three examples including a chaotic system, a mammalian circadian rhythm system and a gastric cancer gene regulatory network. The results show that regulating a small number of biochemical molecules in the network is sufficient to successfully drive the system to the target cyclic attractor by implementing an optimal control strategy.

Optimal Test Assembly in Practice

2013 ◽  
Vol 221 (3) ◽  
pp. 190-200 ◽  
Author(s):  
Jörg-Tobias Kuhn ◽  
Thomas Kiefer
Keyword(s):  
Particle Physics ◽  
Large Scale ◽  
Block Design ◽  
Linear Optimization ◽  
Mixed Integer ◽  
Optimal Test ◽  
Automated Test Assembly ◽  
Test Assembly ◽  
Block Level ◽  
Mixed Integer Linear Optimization

Several techniques have been developed in recent years to generate optimal large-scale assessments (LSAs) of student achievement. These techniques often represent a blend of procedures from such diverse fields as experimental design, combinatorial optimization, particle physics, or neural networks. However, despite the theoretical advances in the field, there still exists a surprising scarcity of well-documented test designs in which all factors that have guided design decisions are explicitly and clearly communicated. This paper therefore has two goals. First, a brief summary of relevant key terms, as well as experimental designs and automated test assembly routines in LSA, is given. Second, conceptual and methodological steps in designing the assessment of the Austrian educational standards in mathematics are described in detail. The test design was generated using a two-step procedure, starting at the item block level and continuing at the item level. Initially, a partially balanced incomplete item block design was generated using simulated annealing, whereas in a second step, items were assigned to the item blocks using mixed-integer linear optimization in combination with a shadow-test approach.

Methods for the Quantification of Salivary Cortisol and of a-amylase in Biosensors and Portable Devices

2018 ◽  
Vol 68 (12) ◽  
pp. 2857-2859
Author(s):  
Cristina Mihaela Ghiciuc ◽  
Andreea Silvana Szalontay ◽  
Luminita Radulescu ◽  
Sebastian Cozma ◽  
Catalina Elena Lupusoru ◽  
...  
Keyword(s):  
Real Time ◽  
Medical Practice ◽  
Salivary Cortisol ◽  
Clinical Studies ◽  
Large Scale ◽  
Psychological Research ◽  
Portable Devices ◽  
Salivary Amylase ◽  
Specificity And Sensitivity

There is an increasing interest in the analysis of salivary biomarkers for medical practice. The objective of this article was to identify the specificity and sensitivity of quantification methods used in biosensors or portable devices for the determination of salivary cortisol and salivary a-amylase. There are no biosensors and portable devices for salivary amylase and cortisol that are used on a large scale in clinical studies. These devices would be useful in assessing more real-time psychological research in the future.

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