The besiege and conquer algorithm has shown excellent performance in single-objective optimization problems. However, there is no literature on the research of BCA multi-objective Therefore, this paper proposes a new to solve grid mechanism, archiving leader selection mechanism are integrated into estimate Pareto optimal solution approach frontier. proposed tested with MOPSO, MOEA/D, NSGAIII benchmark function IMOP ZDT. experiment results show that can obtain competitive terms accuracy solution.

This study presents a comprehensive review of the primary distribution design an advanced network control system, emphasizing its evolution from initial requirements to practical applications. The system solves complex problems power management by combining real-time data analysis, intelligent decision making for resource allocation, rapid fault correction, remote monitoring and optimization methods, all aimed at ensuring stable safe operation grid. Its performance is geared towards fast...

The Tree-Seed Algorithm (TSA) has been effective in addressing a multitude of optimization issues. However, it faced challenges with early convergence and difficulties managing high-dimensional, intricate problems. To tackle these shortcomings, this paper introduces TSA variant (DTSA). DTSA incorporates suite methodological enhancements that significantly bolster TSA’s capabilities. It the PSO-inspired seed generation mechanism, which draws inspiration from Particle Swarm Optimization (PSO)...

This study presents a major advance in grid management: the development and deployment of an integrated network command system for main distribution network. The integrates cutting-edge information technology, including modules such as issuance, intelligent routing, security assurance in-depth data analysis, opening new era refined power management. research focuses on application core technologies communication distributed control system, artificial intelligence big strengthens operation...

The archaeological dating of bronze dings has played a critical role in the study ancient Chinese history. Current archaeology depends on trained experts to carry out dating, which is time-consuming and labor-intensive. For such this study, we propose learning-based approach integrate advanced deep learning techniques knowledge. To achieve this, first collect large-scale image dataset dings, contains richer attribute information than other existing fine-grained datasets. Second, introduce...

Abstract: The epithelial–mesenchymal interactions have an important role in the folliculomorphogenesis and mature hair follicle cycling. dermal papilla, a dense aggregate of specialized dermis‐derived stromal cells located at bottom follicle, is major component hair, which signals follicular epithelial to prolong growth process. However, date, little known about significance specific gene(s) expression papilla with regard their aggregative behaviour In our previous study, differentially...

This paper reports and analyzes measured chip power performance on five process technology generations executing 61 diverse benchmarks with a rigorous methodology. We measure representative Intel IA32 processors technologies ranging from 130nm to 32nm while they execute sequential parallel written in native managed languages. During this period, hardware software changed substantially: (1) vendors delivered multiprocessors instead of uniprocessors, independently (2) developers increasingly...

Advanced hybrid cloud services aim to serve big data applications by bridging multi-provider high performance resources including direct connects, hypervisor bypassing VM interfaces, on premise clusters, parallel storage and speed inter-cloud networks. We present a new "full-stack model driven orchestration" paradigm integrate these diverse through semantic modeling provide complex high-end dynamic orchestrated workflows. also architectural design of real-world orchestration system,...

In controllable generation tasks, flexibly manipulating the generated images to attain a desired appearance or structure based on single input image cue remains critical and longstanding challenge. Achieving this requires effective decoupling of key attributes within data, aiming get representations accurately. Previous research has predominantly concentrated disentangling feature space. However, complex distribution present in real-world data often makes application such algorithms other...

<title>Abstract</title> Winograd-based algorithm is currently one of the optimization methods in convo-lutional computation. It can effectively reduce number multiplications and computational complexity. This paper proposes a convolution accuracy compensation method for low precision vector processor based on architecture multi-core processors. And The we implement multi-level parallel scheme processor. proposed improve adverse effects loss caused by platforms. implemented develops...

While recent test-time adaptations exhibit efficacy by adjusting batch normalization to narrow domain disparities, their effectiveness diminishes with realistic mini-batches due inaccurate target estimation. As previous attempts merely introduce source statistics mitigate this issue, the fundamental problem of estimation still persists, leaving intrinsic shifts unresolved. This paper delves into mini-batch degradation. By unraveling normalization, we discover that inexact largely stem from...

Read-write dependency is an important factor restricting software efficiency. Timing Speculative (TS) a processing architecture aiming to improve energy efficiency of microprocessors. error rate, influenced by the read-write dependency, bottlenecks voltage down-scaling and so TS processors. We proposed method called Read-Write Dependency Aware Register Allocation. It based on aware Interference Graph (RWDIG) conception. Registers are reallocated loosen dependencies, resulting in reduction...

The scale of model parameters and the amount training data is exponentially increasing. It requires more GPU memory with exponential increasement parameters. Recomputation swapping are two main optimization methods that have been extensively studied, there also strategies combine methods. However, most them based on heuristic search strategies, which do not explore complete solution space can't guarantee optimality results. An optimal strategy tensor-level recomputation expected in...

With the access of a large number distributed resources, how to improve aggregation and control ability virtual power plants has become an urgent problem be studied. In this paper, evaluation model regulatory flexibility resources is constructed classify combine flexibly, so as guide plant optimize flexibility.

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The use of intelligent optimization algorithms to optimize vehicle routing problem has become a hot topic in international researches. normal particle swarm (PSO) algorithm is validated evolutionary computation way searching the extreme function, which simple application and quick convergence, but low precision easy premature convergence. In this paper, improved used logistics path by setting inertia factor 0. Through simulation experiment analysis, better convergence (linear convergence)....