The acquisition of somatic mutations by a tumor can be modeled by a type of evolutionary tree. Although many methods have been developed to infer a tumor’s evolutionary history, they can produce conflicting results f...
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ISBN:
(数字)9781665468190
ISBN:
(纸本)9781665468206
The acquisition of somatic mutations by a tumor can be modeled by a type of evolutionary tree. Although many methods have been developed to infer a tumor’s evolutionary history, they can produce conflicting results for a single patient. A consensus tree that reconciles these possible trees is important for understanding the tumor’s evolutionary process. We use integer linear programming to find a consensus tree among multiple plausible tumor evolutionary histories.
Interval regression modeling for a class of uncertain nonlinear system has not been widely studied to data. The proposed modeling method, differently from standard deterministic models, is composed of upper regression...
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ISBN:
(纸本)9781665478977
Interval regression modeling for a class of uncertain nonlinear system has not been widely studied to data. The proposed modeling method, differently from standard deterministic models, is composed of upper regression model (URM) and lower regression model (LRM), and returns an interval output as opposed to a point output (a single value). In this contribution, we address the problem of constructing interval model directly from observed data which is generated from uncertain nonlinear system. The method combines sparsity stemming from the idea of linear programming support vector learning approach, and modeling accuracy guaranteed by measuring the minimization of maximum regarding the selection of approximation error between the actual output and the estimated out (namely Min-Max Optimization). First, quadratic programming problem corresponding to support vector regression (SVR) is transferred to linear programming (LP) problem. Then, the min-max optimization is LP problem within the framework of SVR to form new optimization problem, where the sparsity and optimality of the interval modeling can well be reflected and controlled. The optimization problems with constraints in a form of convex inequality and linear equality are solved by LP. Finally, the sparsity and optimality of the proposed method are demonstrated by the experimental cases using the two indices, the number of utilised support vectors (SVs) and root mean square error (RMSE).
Railway systems help ease traffic in urban areas, especially in densely populated cities. However, rail transit companies have been finding difficulty reducing costs with increasing demand for their services. One of t...
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Railway systems help ease traffic in urban areas, especially in densely populated cities. However, rail transit companies have been finding difficulty reducing costs with increasing demand for their services. One of the primary cost factors in rail transit companies is energy consumption. This study proposes an optimization model for reducing energy consumption in rail transportation systems through linear programming (LP) with the utilization of MATLAB. The study aims to minimize the energy consumed by rail systems within a 30-day interval. The model used in this study used constraints such as the maximum number of trips for the month, the number of trips per 2-hour interval, and the number of passengers, and etc. With the use of the LP using the data from an actual rail transportation system, the amount of energy consumed by the rail system can be minimized to 639,480 KW from 824,300 KW.
We present an approach to Fuglede’s conjecture in Z3p using linear programming bounds, obtaining the following partial result: if A ⊆ Z3p with p2 − p√p + √p 2, then A is not *** Codes 43A46, 90C05, 52C22, 11L03, 20...
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The Cohn-Elkies linear program for sphere packing, which was used to solve the 8 and 24 dimensional cases, is conjectured to not be sharp in any other dimension d > 2. By mapping feasible points of this infinite-di...
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This paper shows a methodology to determine the optimal number of photovoltaic panels, batteries and inverters of an autonomous photovoltaic system to meet the electrical demand of a residence at the lowest total life...
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ISBN:
(数字)9781665452137
ISBN:
(纸本)9781665452144
This paper shows a methodology to determine the optimal number of photovoltaic panels, batteries and inverters of an autonomous photovoltaic system to meet the electrical demand of a residence at the lowest total life cycle cost possible, an economic objective function that includes the initial costs of capital, replacement, operation and maintenance of the system components. The case study consists of the electrification of a rural house located in the State of Veracruz, Mexico. The problem was solved through the development of a linear programming model in MATLAB, considering that the state of charge of the battery bank must be kept at adequate levels to the preservation of its useful life.
Velocity Planning for self-driving vehicles in a complex environment is one of the most challenging tasks. It must satisfy the following three requirements: safety with regards to collisions;respect of the maximum vel...
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This paper is a follow-up to a previous work where we defined and generated the set of all possible compromises of multilevel multiobjective linear programming problems (ML-MOLPP). In this paper, we introduce a new al...
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Motivated by hiring pipelines, we study three selection and ordering problems in which applicants for a finite set of positions must be interviewed or sent offers. There is a finite time budget for interviewing/sendin...
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In this fast-growing modernization, excess carbon emission plays a crucial role in climate change. Targeting and experimenting with sustainable ways of Carbon neutrality and management is the pathway toward a greener ...
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ISBN:
(纸本)9798350398106
In this fast-growing modernization, excess carbon emission plays a crucial role in climate change. Targeting and experimenting with sustainable ways of Carbon neutrality and management is the pathway toward a greener society. Data show that factories and industries take a high market stake in carbon emission and management. In actions, Governments defined a limit for carbon emissions to each organization which is called carbon credit. Every organization must focus on reducing carbon emissions. This is a critical task for each organization, In some cases, it is still not possible to explore other sustainable options. An innovative solution proposed for the above scenario is to implement a real-time platform that can provide insights into the most up-to-date emission statistics of the organization. This paper provides advanced analytics and precise proactive planning and actions in the simplest form and a discussion on future elaborations and insights about conclusions. By finding the minimum optimal emission values of each emission source, organizations can maintain carbon emissions without exceeding their carbon credit. Also, how industries and factories can create a smart carbon optimization system that can create an even greener society.
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