The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

Abstract: Metaheuristic algorithms have demonstrated strong effectiveness in solving complex real-world optimization problems. This paper presents two discrete metaheuristic approaches for the ...

Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization. For B2Bs and brands selling ...

Introduction: Optimizing fracturing parameters under multi-factor, complex conditions remains challenging in low-permeability reservoirs. Methods: We extract stage-aware construction-curve features, ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

Abstract: To achieve high-precision engineering design and improve the optimization efficiency of beam optical systems, this paper proposes a two-stage optimization method based on intelligent ...

Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...

With the rise of 3D printing and other advanced manufacturing methods, engineers can now build structures that were once impossible to fabricate. An emerging design strategy that takes full advantage ...