按方法、领域与证据探索科学。

Agent-based multi-objective optimization

Agent-based multi-objective optimization (ABMOO) embeds autonomous agents inside a simulation environment and evolves their behavior or parameters to simultaneously optimize two or more conflicting objectives, yielding a Pareto-efficient frontier of solutions rather than a single optimum. It is suited to complex adapti

simulation

Agent-based scenario analysis

Agent-based scenario analysis embeds agent-based simulation models inside a structured scenario planning framework. Researchers define two to four contrasting future scenarios, configure agent populations and environmental rules to reflect each scenario's assumptions, run the simulation under each condition, and compar

simulation

Agent-based sensitivity analysis

Agent-based sensitivity analysis (ABSA) applies sensitivity analysis techniques to agent-based models (ABMs) to determine which input parameters most strongly influence emergent outputs. Because ABMs are stochastic and nonlinear, standard analytical derivatives are unavailable; ABSA uses designed simulation experiments

simulation

Agent-based system dynamics

Agent-based system dynamics (AB-SD) is a hybrid simulation paradigm that couples agent-based modeling (ABM) at the micro level with system dynamics (SD) stock-and-flow structures at the macro level. This allows researchers to capture emergent individual behavior and feedback-driven aggregate dynamics within a single co

software engineering

Agile Velocity Tracking

Velocity tracking measures the amount of work (typically story points or tasks) a team completes in a sprint, enabling capacity planning, release forecasting, and identification of process improvements. Introduced in Scrum methodology by Schwaber (2002), velocity provides empirical data for realistic sprint planning an

aerospace

AHRS

An Attitude Heading Reference System (AHRS) is a complete inertial navigation subsystem that estimates and outputs the three-dimensional orientation (attitude) and heading of a vehicle or platform. AHRS combines measurements from accelerometers, gyroscopes, and often magnetometers through sensor fusion algorithms (typi

model evaluation

Akaike Information Criterion

The Akaike Information Criterion is an information-theoretic measure for model selection that balances goodness of fit against model complexity. Introduced by Hirotugu Akaike in 1974, AIC estimates the relative quality of models for a given dataset, penalizing additional parameters to prevent overfitting.

telecommunications

Alamouti Code

The Alamouti code is an elegant space-time coding scheme that provides full transmit diversity using two antennas and a simple linear receiver. Introduced by Siavash Alamouti in 1998, it requires no channel state information at the transmitter, achieves the same bit-error rate as a single-antenna system with receiver d

deep learning

AlexNet

AlexNet is a deep convolutional neural network (CNN) introduced by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton in 2012. It won the ImageNet Large Scale Visual Recognition Challenge (ILSVRC 2012) with a top-5 error rate of 15.3%, outstripping the runner-up by more than 10 percentage points and reigniting broad

applied physics

Ambisonics

Ambisonics is a full-sphere spatial audio encoding and reproduction technique that captures and reproduces three-dimensional sound fields. Developed by Michael Gerzon in the 1970s, it uses spherical harmonics to represent sound at all directions around a central point. Unlike surround systems that use discrete channels

genetics

Ancestral State Reconstruction

Ancestral state reconstruction (ASR) is a phylogenetic method that infers the character states (trait values or evolutionary features) of extinct ancestors by analyzing patterns of variation in extant (living) species. Developed by Wayne Maddison and colleagues in the 1990s, ASR uses the phylogenetic tree and observed

particle physics

Anti-kT Jet Algorithm

The anti-kT jet algorithm, introduced by Cacciari and Salam in 2008, is a sequential recombination jet clustering algorithm widely used in high-energy physics to group final-state particles into jets. Unlike earlier algorithms, anti-kT produces jets with regular cone-like geometries in transverse momentum-rapidity spac

machine learning

Apriori Algorithm

The Apriori algorithm, introduced by Agrawal and Srikant in 1994, is the foundational method for discovering frequent itemsets and association rules in transactional databases. It uses a breadth-first, level-wise search guided by the anti-monotone property of support to efficiently enumerate all item combinations that

software engineering

Architecture Smell Detection

Architecture smells are recurring patterns in system structure that indicate potential design problems. Introduced by García et al. (2009), these patterns signal violations of architectural principles (modularity, independence, abstraction) at system scale. Detection combines code metrics, dependency analysis, and patt

text mining

Argument Mining

Argument mining is a natural-language-processing task that automatically detects claims, premises and the argumentative structures that link them within text. Consolidated as a field by Lippi and Torroni's 2016 state-of-the-art survey, it is applied to scientific writing, legal documents and debate analysis to turn fre

text mining

Aspect-Based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) is a fine-grained natural-language-processing task that detects sentiment separately for each aspect or feature mentioned in a text — such as a product's quality, price, or service — rather than scoring the document as a whole. It was consolidated as a shared task by Pontiki et al

machine learning

Association Rule Mining

Association Rule Mining is an unsupervised data-mining technique that discovers co-occurrence patterns among items in transactional datasets. Formally introduced by Agrawal, Imieliński, and Swami in 1993, and refined with the landmark Apriori algorithm by Agrawal and Srikant in 1994, it identifies rules of the form X ⇒

machine learning

Association Rules

Association rule learning is an unsupervised technique that discovers co-occurrence patterns — 'if X then Y' implications — within large transactional datasets. Originally formalized by Agrawal, Imielinski, and Swami (1993) for supermarket basket analysis, it is now widely applied in e-commerce recommendation, health i

astronomy

Asteroseismology

Asteroseismology is the study of stellar oscillations—tiny brightness and radial velocity variations caused by sound waves resonating inside stars. Proposed by Roger Ulrich in 1970 and established as a major field by the Kepler and TESS space telescopes, asteroseismology provides unprecedented precision in determining

astronomy

Astrometry (Parallax)

Astrometric parallax is the foundational geometric method for measuring distances to nearby stars, based on observing the apparent shift in a star's position as Earth orbits the Sun. First successfully demonstrated by Friedrich Wilhelm Bessel in 1838 for the star 61 Cygni, parallax remains the most direct and reliable

genetics

ATAC-seq Analysis

ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) is a method for profiling the landscape of chromatin accessibility genome-wide. Developed by Buenrostro and colleagues in 2013, ATAC-seq uses hyperactive transposase to tag open, accessible chromatin regions, enabling rapid and sensitive identificat

spectroscopy

ATR-FTIR

Attenuated Total Reflectance (ATR) Fourier Transform Infrared (FTIR) spectroscopy is a variant of conventional FTIR that measures infrared absorption through evanescent-wave interrogation of samples in direct contact with a high-refractive-index crystal. Developed by Harrick and Fahrenfort in the 1960s, ATR-FTIR is now

deep learning

Attention Mechanism

The attention mechanism, introduced by Bahdanau, Cho and Bengio in 2015 and refined by Luong, Pham and Manning the same year, lets a sequence decoder dynamically learn which of the encoder's outputs to focus on at each step. Before the Transformer, it substantially improved machine-translation quality by freeing models

music information retrieval

Audio Fingerprinting

Audio fingerprinting is a technique for creating a compact, robust identifier (fingerprint) for audio recordings that uniquely represents the content while being tolerant to modifications such as compression, noise, or time-shifting. Introduced by Haitsma and Kalker (2002), it underlies music identification services li

text mining

Authorship Attribution

Authorship attribution is the task of identifying the most probable author of an anonymous or disputed text by analysing its stylistic fingerprint. Rooted in the statistical work of Mosteller and Wallace on the Federalist Papers (1964), the field was systematically surveyed and formalised by Stamatatos (2009), who cata

deep learning

Autoencoder

An autoencoder is an encoder-decoder neural network, popularised by Hinton and Salakhutdinov in 2006, that compresses data into a low-dimensional latent code and then reconstructs it, enabling dimensionality reduction and anomaly detection. By learning to rebuild its own input through a narrow bottleneck, it discovers

machine learning

Autoencoder Anomaly Detection

Autoencoder anomaly detection trains a neural network to compress and then reconstruct normal data. Because the model has only ever learned what normal looks like, anomalous inputs produce noticeably higher reconstruction errors — and those errors become the anomaly score. The method requires no labeled anomalies and s

text mining

Automated Essay Scoring

Automated Essay Scoring (AES) is a natural-language-processing task in which a computational model assigns scores to student-written essays across dimensions such as grammatical correctness, coherence, content richness, and organisation — replicating, at scale, what a human rater would do. The approach was formalised a

numerical methods

Automated Theorem Proving

Automated Theorem Proving (ATP) is a field of artificial intelligence and mathematical logic dedicated to mechanically proving mathematical theorems in formal systems. Developed by John Robinson in 1965 with the resolution principle, ATP underpins modern verification tools like SAT/SMT solvers and is foundational to fo

music information retrieval

Automatic Music Transcription

Automatic music transcription is the task of converting audio recordings into symbolic music notation (e.g., scores with note pitch, onset, and duration). Formalized as a research problem by Klapuri (2008), it represents one of the most challenging tasks in music information retrieval. Transcription enables music educa

text mining

Automatic Text Evaluation

Automatic text evaluation is a family of reference-based metrics used to measure the quality of machine-generated text — such as translations, summaries, or natural-language-generation (NLG) outputs — by comparing them to one or more human-written reference texts. Pioneered by Papineni et al. with BLEU in 2002, the fie

aerospace

B-Dot Controller

The B-Dot controller (magnetic B-dot control law) is a simple, robust spacecraft attitude control method that uses the rate of change of Earth's magnetic field measured onboard to generate a magnetic dipole moment. Developed in the 1980s, the B-Dot law damps spacecraft angular momentum without requiring a complex attit

computer vision

Background Subtraction

Background subtraction is a video processing technique that separates moving foreground objects from a static or slowly changing background by comparing each frame to a learned or estimated background model. Widely used in video surveillance and motion detection, background subtraction enables robust foreground detecti

control theory

Backstepping Control

Backstepping is a systematic nonlinear control design method that decomposes a complex nonlinear system into simpler subsystems and designs a controller recursively, layer by layer, ensuring stability at each step. Developed by Krstic, Kanellakopoulos, and Kokotovic, backstepping enables control of nonlinear systems wi

model evaluation

Balanced Accuracy

Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regardless of class frequency in the dataset.

acoustics

Bark and Mel Scales

Bark and Mel scales are perceptual frequency scales that map physical frequency (Hz) to perceived pitch and auditory perception. Formalized by Zwicker (Bark, 1961) and Stevens (Mel, 1937), these non-linear scales reflect how the human ear processes sound. Bark scale divides hearing into 24 critical bands; Mel scale mod

meteorology

Barnes-Cressman Analysis

Barnes-Cressman analysis is an objective interpolation method that creates gridded meteorological fields from irregularly spaced observations (station data, radiosonde profiles, buoys). It is widely used for synoptic analysis, quality control, and initialization of numerical weather models.

astronomy

Baryon Acoustic Oscillations

Baryon Acoustic Oscillations are imprints of sound waves in the early universe that appear as a characteristic scale in the large-scale distribution of galaxies today. First predicted theoretically by Piet Peebles and Joseph Yu in 1970, and detected observationally by the Sloan Digital Sky Survey in 2005, BAO provides

geoscience

Basin Subsidence Analysis

Basin subsidence analysis is the quantitative study of how sedimentary basins deepen over geological time, driven by tectonics, isostasy, and load. Formalized by McKenzie (1978) and Sclater and Christie (1980), this method reveals the mechanical causes of basin development, predicts subsurface temperature and pressure

deep learning

Batch Normalization

Batch Normalization is a training technique introduced by Sergey Ioffe and Christian Szegedy in 2015 that normalizes the pre-activation outputs of each layer using the mean and variance computed over the current mini-batch. By stabilizing the input distribution to each layer throughout training, it substantially reduce

thermodynamics

Battery Equivalent Circuit Model

The Battery Equivalent Circuit Model (ECM) represents battery electrochemical behavior using an electrical circuit analogy. It includes an ideal voltage source (open-circuit voltage dependent on state of charge), internal resistance(s) for ohmic losses, and capacitive/resistive elements for transient response. ECM enab

biomechanics

BCI Motor Imagery

Brain-computer interface (BCI) using motor imagery decodes the intent to move from brain activity (typically EEG) recorded while subjects imagine movement without actual muscle contraction. Pioneered by Gert Pfurtscheller and colleagues, motor imagery BCIs enable communication and control for paralyzed patients and enh

particle physics

BDT Particle Identification

Boosted Decision Trees (BDTs) are powerful multivariate classifiers used in particle physics to distinguish between different particle types based on detector signatures. By combining many weak decision trees through adaptive boosting, BDTs achieve superior discrimination power compared to simple cuts, enabling improve

acoustics

Beamforming

Beamforming is a spatial signal processing technique that uses microphone arrays to selectively enhance sound from a desired direction while suppressing sounds from other directions. Formalized by Van Veen and Buckley in 1988, beamforming is fundamental to hands-free speech communication, hearing aids, sonar, radar, an

music information retrieval

Beat Tracking

Beat tracking is an algorithm for automatically identifying the temporal positions of musical beats in audio recordings. It has been widely studied since the early 2000s, particularly for rhythm analysis and music synchronization applications. The problem is central to music information retrieval and essential for musi

acoustics

BEM Acoustics

The Boundary Element Method (BEM) is a numerical technique for solving acoustic wave equations in complex geometries. Unlike finite element methods (FEM) that mesh entire volumes, BEM discretizes only the acoustic boundaries (surfaces), reducing computational cost and memory. First applied to acoustics by Burton and Mi

civil engineering

BEM Geomechanics

The boundary element method (BEM) for geomechanics is a numerical approach that solves problems by discretizing only the boundary of the domain, using analytical solutions for the interior. Introduced by Brebbia in 1978 and refined for geotechnical applications by Crouch and Starfield, BEM is particularly effective for

oceanography

Benthic Index of Biotic Integrity

The Benthic Index of Biotic Integrity (B-IBI) is an ecological assessment metric that measures the health and integrity of benthic (seafloor) communities based on the composition, abundance, and diversity of benthic fauna. Developed by James Karr in 1981 for freshwater fish assemblages and later adapted for marine bent

text mining

BERT Embeddings

BERT-based text embeddings, introduced by Devlin and colleagues at Google AI in 2019, turn text into context-sensitive dense vectors using a bidirectional Transformer encoder. Because the meaning of a word shifts with its context, BERT produces richer representations than static methods such as Word2Vec or topic models

deep learning

BERT Fine-Tuning

BERT fine-tuning, building on the BERT model introduced by Devlin and colleagues in 2019, re-trains a pre-trained BERT model on a small labelled dataset for a target task such as classification, named-entity recognition, or question answering. Through transfer learning it reaches high performance even with relatively l

text mining

BERTopic

BERTopic is a neural topic-modeling pipeline introduced by Maarten Grootendorst in 2022. It combines BERT-based contextual embeddings with UMAP dimensionality reduction and HDBSCAN clustering to produce coherent, dynamic topics, achieving higher topic coherence than classic topic models.

materials science

BET Surface Area

Brunauer-Emmett-Teller (BET) Surface Area Analysis is a technique for measuring the specific surface area of solids by analyzing their nitrogen adsorption isotherms. Developed by Brunauer, Emmett, and Teller in 1938, BET theory extends monolayer adsorption (Langmuir) to multilayer adsorption, enabling quantification of

network analysis

Betweenness Centrality

Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other

thermodynamics

Betz Limit

The Betz Limit states that no wind turbine can extract more than 59.3% of the kinetic energy from flowing wind, regardless of design. This fundamental thermodynamic limit arises because extracting energy slows the wind, which then blocks further energy extraction. Albert Betz derived this limit in 1920 from momentum an

telecommunications

BGP

BGP is the de facto standard routing protocol for interconnecting autonomous systems (ASs) on the Internet. Since its introduction in 1989, BGP has scaled the Internet to millions of routers and trillions of destinations. BGP is path-vector-based, using a flexible policy system to control route propagation and selectio

deep learning

Bidirectional RNN

A Bidirectional RNN, introduced by Schuster and Paliwal in 1997, processes a sequence in both forward and backward directions so that every position has access to its full surrounding context. With LSTM or GRU cells (BiLSTM/BiGRU) it is the standard approach for named-entity recognition, sequence labelling, and speech

numerical methods

Binary Decision Diagram

Binary Decision Diagrams (BDDs) are a canonical, memory-efficient representation of Boolean functions developed by Randal Bryant in 1986. A BDD is a directed acyclic graph encoding all variable assignments and results; reduced BDDs are unique for each function and enable efficient manipulation of combinatorial logic in

network analysis

Bipartite Network Analysis

Bipartite network analysis, formalised by Borgatti and Everett in 1997, is a graph-structural method for studying networks in which nodes are divided into two disjoint sets — actors and events — and edges exist only between sets, never within them. It is the natural framework for author–paper, patient–disease, user–pro

machine learning

BIRCH

BIRCH is a scalable, incremental clustering algorithm introduced by Zhang, Ramakrishnan, and Livny in 1996. It is designed to cluster very large datasets — potentially larger than available memory — in a single pass, by compressing the data into a compact in-memory summary structure called a CF-tree (Clustering Feature

aerospace

Blade Element Momentum Theory

Blade element momentum theory (BEM) is a fundamental method for analyzing rotor performance by combining blade element aerodynamics with momentum conservation. Developed initially by Froude and refined by Glauert and Leishman, BEM decomposes a rotor into radial blade elements, computes local aerodynamic forces, and sum