Results 81 to 90 of about 18,556 (186)
Why raw yield data are better than relative yield in informing agronomic and economic decisions
Abstract While relative yield is widely used for its comparability, normalization can cause significant information loss. This study reframes yield metric selection as a model evaluation problem to determine the most accurate representation of crop response. We evaluated seven yield metrics with three agronomic models, comparing estimates of a critical
Falin Sun +4 more
wiley +1 more source
On the complexity of nonlinear mixed-integer optimization [PDF]
This is a survey on the computational complexity of nonlinear mixed-integer optimization. It highlights a selection of important topics, ranging from incomputability results that arise from number theory and logic, to recently obtained fully polynomial ...
Köppe, Matthias
core
Abstract Longitudinal data from repeated measurements are commonly used in social and behavioral sciences to study students’ growth. When scores are assigned by raters, they become subject to rater effects such as variability in rater stringency. Therefore, in longitudinal assessments with rater‐assigned scores, valid inference on growth requires ...
Yun Kyung Kim, Sijia Huang, Eun Hye Ham
wiley +1 more source
The optimization of investment portfolios represents a pivotal task within the field of financial economics. Its objective is to identify asset combinations that meet specified criteria for return and risk.
Mirko Mattesi +6 more
doaj +1 more source
Power Load Management as a Computational Market [PDF]
Power load management enables energy utilities to reduce peak loads and thereby save money. Due to the large number of different loads, power load management is a complicated optimization problem.
Akkermans, Hans, Ygge, Fredrik
core +6 more sources
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin +4 more
wiley +1 more source
Solving Quadratic Unconstrained Binary Optimization with divide-and-conquer and quantum algorithms
Quadratic Unconstrained Binary Optimization (QUBO) is a broad class of optimization problems with many practical applications. To solve its hard instances in an exact way, known classical algorithms require exponential time and several approximate methods have been devised to reduce such cost.
openaire +2 more sources
On some features of quadratic unconstrained binary optimization with random coefficients
Abstract Quadratic Unconstrained Binary Optimization (QUBO or UBQP) is concerned with maximizing/minimizing the quadratic form $$H(J, \eta ) = W \sum _{i,j} J_{i,j} \eta _{i} \eta _{j}$$ H ...
Isopi, Marco +2 more
openaire +5 more sources
Improving the Solving of Optimization Problems: A Comprehensive Review of Quantum Approaches
Optimization is a crucial challenge across various domains, including finance, resource allocation, and mobility. Quantum computing has the potential to redefine the way we handle complex problems by reducing computational complexity and enhancing ...
Deborah Volpe +2 more
doaj +1 more source

