Expected improvement (EI) is one of the most widely-used acquisition functions in Bayesian optimization (BO). Despite its proven success applications for decades, important open questions remain on theoretical convergence behaviors and rates EI. In this paper, we contribute to theories EI three novel critical area. First, consider objective that are under Gaussian process (GP) prior assumption, whereas existing works mostly focus reproducing kernel Hilbert space (RKHS). Second, establish...

The purpose of the present research is to study approaches formation an interactive learning environment for effective music in Chinese primary and secondary schools. Initially, defined that most students had mastered average level knowledge before intervention. programs school focused on studying aspects musical notation ability identify it (27%). involved development a modified curriculum. elaborated program contained various technologies, playfully information, direct interaction from...

.An optimization algorithm for nonsmooth nonconvex constrained problems with upper- \(\mathcal{C}^2\) objective functions is proposed and analyzed. Upper- a weakly concave property that exists in difference of convex (DC) arises naturally many applications, particularly certain classes solutions to parametric e.g., recourse stochastic programming projection onto closed sets. The can be viewed as an extension sequential quadratic (SQP) objectives or simplified bundle method. It globally...

Purpose The purpose of this paper is to evaluate the service quality university library more accurately and dynamically improve efficiency library. realizes quantified representation overcomes shortcoming traditional evaluation system, which does not consider reader’s identity cannot be evaluated separately. In addition, according function configuration each department library, a relation between parameter its organization structure built. According results chain relations, some suggestions...

The total output value of the construction industry (TOVCI) reflects its own development level to a certain extent. An accurate prediction industry’s is beneficial government’s dynamic regulation. grey model widely used for simple calculation process and high accuracy. Based on TOVCI China from 2017 2020, this paper constructs an FGM (1,1) model, calculates r by simulated annealing algorithm, forecasts in next few years. At present, Particle Swarm Optimization algorithm (PSO) employed...

Background: Noise damage and its health effects have gained traction of researchers governments. However, challenges persist due to the paucity comprehensive studies integrating quietness naturalness into assessment urban sound quality.Goals: This study developed an innovative soundscape quality index that simultaneously assesses both in a soundscape. Accordingly, we conducted mapping, influential mechanisms analysis, identification priority zones for environment management.Approaches: We...

In order to overcome the shortcomings of traditional methods for detecting users' reading state in a smart library building, more effective method is proposed. this method, some posture characteristic parameters are put forward represent after analyzing relationship between and their state. And then, one stripe light illuminating system 3-D designed by developing projector video monitoring system, which, image with periodic modulation received on system. At last, two images extracted time...

Bayesian optimization (BO) with Gaussian process (GP) surrogate models is a powerful black-box method. Acquisition functions are critical part of BO algorithm as they determine how the new samples selected. Some most widely used acquisition include upper confidence bound (UCB) and Thompson sampling (TS). The convergence analysis algorithms has focused on cumulative regret under both frequentist settings for objective. In this paper, we establish pointwise bounds prediction error GP setting...

With the continuous changes in consumer demand and market, publishing enterprises are facing challenge of transformation upgrading. Business model innovation, as one important measures for to achieve self is great significance long-term sustainable development. How innovate business models value creation also a common problem that companies urgently need solve. This paper will conduct research on leading brand influence, marketing model, production method Chinese book industry's professional...

In Supply Chain Management (SCM), product classification and demand forecasting are crucial pillars to ensure companies have production in the right category quantity for long-term profitability. Due COVID-19 from 2019, automobile industry has been seriously negatively affected as dropped dramatically. Therefore, it is necessary make reasonable accurate facilitate SCM reduce unpopular manufacture unnecessary storage costs. this paper, Canada market chosen with period 1946 2022. To classify a...

The aim of the study is to identify possibility using mobile online technologies for teaching ethnomusicology and assess their impact on student performance. research was conducted at Music College Zhejiang University, China. sample consisted 106 students: 52 students in 2018/2019 academic year 54 2019/2020 year. majority (82.5%) are convinced that this technology should become part environment a modern course ethnomusicology. findings will help improve policies strategies integration classroom.

A sequential quadratic programming (SQP) algorithm is designed for nonsmooth optimization problems with upper-C^2 objective functions. Upper-C^2 functions are locally equivalent to difference-of-convex (DC) smooth convex parts. They arise naturally in many applications such as certain classes of solutions parametric problems, e.g., recourse stochastic programming, and projection onto closed sets. The proposed conducts line search adopts an exact penalty merit function. potential...

An optimization algorithm for a group of nonsmooth nonconvex problems inspired by two-stage stochastic programming is proposed. The main challenges these include (1) the lack popular lower-type properties such as prox-regularity assumed in many algorithms, (2) objective can not be analytically expressed and (3) evaluation function values subgradients are computationally expensive. To address challenges, this report first examines that exist problems, specifically upper-C^2 objectives. Then,...

We present a scalable optimization algorithm and its parallel implementation for two-stage stochastic programming problems of large-scale, particularly the security constrained optimal power flow models routinely used in electrical grid operations. Such can be prohibitively expensive to solve on industrial scale with traditional methods or serial. The decomposes problem into first-stage second-stage subproblems which are then scheduled asynchronously efficient evaluation parallel....