750 results about "Information analysis" patented technology

The invention relates to the field of enterprise risk early warning analysis, in particular to an intelligent risk early warning method and system based on multi-dimensional data analysis. The method comprises the following steps: acquiring a multi-dimensional enterprise data stream, performing heterogeneous index information analysis and logic hierarchy reconstruction, and constructing an enterprise running state sensing map; performing multi-index local fluctuation amplitude calculation on the enterprise operation state sensing map, and performing dynamic disturbance feature mining to construct a risk disturbance spectrogram; performing deep semantic analysis and node state abrupt change feature analysis on the risk disturbance spectrogram to generate a dynamic transition type of an abrupt change node; and performing full-period time sequence tracing on the risk disturbance spectrogram, performing potential risk node prediction based on the dynamic transition type, and identifying other potential risk propagation ports. Through accurate and efficient enterprise risk perception, the risk intervention decision is made in advance, and the anti-risk capability and the operation stability of the enterprise are improved.

The invention discloses a document analysis and query method based on a knowledge graph, and the method comprises the steps: carrying out the part-of-speech tagging of a received to-be-analyzed document, and obtaining a part-of-speech tagging result; extracting knowledge element information from the part-of-speech tagging result based on a preset power grid domain ontology knowledge base, and constructing an initial knowledge graph based on the knowledge element information; combining nodes in the initial knowledge graph to obtain a fused knowledge graph; constructing a mapping table according to the fused knowledge graph, and generating a candidate query template set based on the mapping table; receiving a natural language query statement input by a user, selecting a target query template from the candidate query template set based on the natural language query statement, and generating a target query statement; querying from the fused knowledge graph by using the target query statement, and outputting a query result; according to the method, the accuracy and comprehensiveness of information analysis can be effectively improved, the query intention of the user can be accurately understood, and the accurate query and analysis requirements of professionals on project documents are met.

The invention discloses a dialogue type data analysis method and device, a storage medium and electronic equipment, and relates to the technical field of data analysis. The method comprises the steps that a natural language text input by a user is acquired; obtaining corresponding semantic pre-analysis information based on the natural language text; matching a corresponding mode mapper based on the semantic pre-analysis information; obtaining corresponding semantic information based on a mode mapper; converting the semantic information into corresponding semantic information conversion parameters; analyzing the semantic information conversion parameter to obtain an index value corresponding to the to-be-queried index; performing anomaly detection on the index value corresponding to the to-be-queried index; and performing analysis result display on the index value corresponding to the to-be-queried index passing the anomaly detection. According to the method, information arrangement and information analysis are carried out on the natural language text input by the user, the intention of the user is known, the index needing to be queried by the user is fed back, the operation complexity is reduced, the interactivity and the real-time performance are improved, and convenience is provided for data analysis work.

The invention relates to the technical field of data sharing security, in particular to a government affair data security sharing method and system based on a block chain technology. The method comprises the following steps: acquiring user service handling information, analyzing user service requirements according to the user service handling information, and determining target multi-level department chain information; according to the target multi-level department chain information, performing multi-level encryption anchoring uplink storage on the user service handling information, and determining service multi-level department chain information; and based on an intelligent contract driving strategy, according to the user service demand and the service multi-level department chain information, performing multi-department chain type cooperative processing on the user service demand, and determining and outputting a government affair processing result. According to the application, the data sharing security among different hierarchy departments in the government affair processing process is improved, good balance between data security and government affair processing is effectively guaranteed, the working efficiency and experience of users are improved, and the government affair electronization process and efficient configuration of social resources are promoted.

The invention discloses a network security information analysis and statistics method based on a regulation and control cloud platform. Protocol identification, standardized mapping and blood relationship marking of multi-source security equipment data are realized through an edge layer protocol adaptation cluster and a metadata self-registration mechanism; constructing a real-time streaming and batch processing dual-channel framework based on regulation and control of cloud platform container resources, and fusing to generate a standardized security event object with a frequency weight and a hazard coefficient; designing a main ring-emergency ring double-path decision closed loop, respectively processing conventional events and high-risk threats, and realizing knowledge base iteration; extracting features by using a containerized architecture in combination with an XGBoost + isolated forest integrated model, detecting threats and generating rules; and a space-time-system-risk four-dimensional visualization engine is constructed, attack path drawing, event evolution display and high-risk area prediction are realized, and a management closed loop is formed. According to the network security information analysis and statistics method based on the regulation and control cloud platform, the intelligence and automation level of network security information analysis and statistics is improved.

The invention belongs to the technical field of electric power system information processing, and particularly relates to an electric power information analysis method based on big data, through semantic fusion of multi-source heterogeneous data and dynamic feature mining of a time sequence attention mechanism, in a load prediction scene, compared with a traditional single data source model, the electric power information analysis efficiency is improved. After the meteorological data, the user power consumption behavior data and the power grid operation data are fused, the prediction average error rate is reduced; in an equipment fault early warning scene, through multi-dimensional correlation analysis of vibration signals, oil temperature data and environmental factors, transformer latent faults can be early warned in advance, and the fault identification accuracy is improved; meanwhile, a self-adaptive modeling engine and a closed-loop feedback mechanism enable the system to have a self-evolution capability: when the power grid topology is adjusted or the new energy grid-connected proportion is changed, the model does not need to be manually retrained, and self-adaptive adaptation can be completed in two scheduling cycles through dynamic feature weight adjustment and meta-learner parameter optimization, so that the analysis performance is maintained to be stable.

The invention discloses a document knowledge base LLM intelligent question and answer method, device and equipment and a storage medium. The method comprises the steps that dynamic partitioning is conducted on a to-be-processed document, and vectorization and index storage are conducted on knowledge blocks; vector retrieval and keyword retrieval are carried out according to the natural language question, a vector retrieval result and a keyword retrieval result are fused, an answer is obtained through LLM, and the answer is fed back to a user after being safely filtered; when it is detected that the to-be-processed document is updated, the vector library and the index are synchronously updated, and the cue word template and the partitioning strategy are periodically optimized, so that the problem of form picture information loss can be solved, the integrity of document information analysis is guaranteed, the situation that the partitioning strategy is single is avoided, the multi-hop recall rate is increased, and the problem of semantic missing is avoided; a partitioning mechanism is reasonable, retrieval precision is improved, updating cost is reduced, data security is improved, implementation is convenient, universality is good, and the speed and efficiency of LLM intelligent question answering of the document knowledge base are improved.

The invention belongs to the technical field of computer information processing, and relates to a scientific research performance information analysis and evaluation system and a processing method thereof.The scientific research performance information analysis and evaluation system comprises a data collection module, a weight distribution module, a real-time feedback module and an execution engine function module; weight distribution receives the first signal and analyzes a current strategic target priority identifier and a historical performance evaluation record contained in the first signal, a weight parameter space dynamically matched with a target priority is constructed through an online learning algorithm, and a second signal containing a real-time weight mapping relation is generated; real-time feedback is carried out, a multi-dimensional performance evaluation matrix is constructed based on the weight mapping relation in the second signal, and a third signal is generated; the execution engine receives the third signal, analyzes an abnormal positioning code of the third signal, and aggregates intervention records in a period to form a fourth signal; according to the method, the defects that traditional performance information analysis depends on static weight, the data dimension is single, and real-time dynamic adjustment is lacked can be overcome, and the analysis efficiency is improved.

The invention provides a bulk cargo wharf intelligent equipment scheduling system and method, equipment and a storage medium. The scheduling system comprises a data acquisition module; an information analysis and strategy generation module; a joint scheduling calculation module; a scheduling execution module; an execution feedback module; a model updating module; and a rule induction module. According to the method, a closed-loop liberalization system fusing semantic understanding, strategy generation and scheduling execution is constructed, so that the problem that unstructured information cannot be effectively utilized by a scheduling system is solved; scheduling parameters can be accurately extracted from unstructured data, even scheduling characteristic parameters are directly extracted from the unstructured data and structured scheduling strategy suggestions are generated, the data threshold of system intelligent transformation is reduced, a scheduling model is driven together with the structured parameters, a feedback learning mechanism is introduced, and the scheduling efficiency is improved. And efficient, intelligent and self-learning management of equipment scheduling is realized, so that the system can adapt to complex and variable port operation environments, and has good expansibility and generalization ability.

The invention discloses a data analysis processing method and system based on multi-source data fusion, and relates to the technical field of data analysis fusion processing. Comprising the following steps: data acquisition and preprocessing: acquiring multi-source data, including user behavior data, content data and social data, related to APP pushing and cultural transmission from a plurality of data sources such as social software and an internet platform, after acquisition, preprocessing the multi-source data, generating preprocessed data, and establishing a dynamic credibility evaluation model; according to the method, the dynamic credibility evaluation model is established to distribute the weight for the data source, so that the interference of low-credibility data on the analysis result is avoided, and the information analysis of the user interest intensity, the content credibility and the cultural value based on the fused data is more accurate; therefore, a more reliable basis is provided for making an APP push strategy and a cultural transmission scheme.

The invention relates to the technical field of multi-source information analysis, in particular to a niobium-tantalum metal ore metallogenic evaluation system based on multi-source information analysis, which comprises a geologic structure association module, a mineral distribution interpretation module, a metallogenic environment adaptation module, a spatial feature analysis module and a potential region judgment module. According to the method, by introducing a multi-source data analysis and fusion method, the evaluation precision and comprehensive capability of resource exploration are effectively improved, analysis after information fusion is combined with relevance and spatial modes of different data types, it is ensured that mineralization potential evaluation is more accurate, the limitation of a single data source and manual analysis is overcome, and the method is suitable for popularization and application. According to the method, the identification precision and reliability of the mineralization law are improved, the potential area can be identified more accurately, resource potential analysis is optimized in combination with the adaptability of the mineralization environment, the efficiency and accuracy of determining the mineralization area are remarkably improved, the problems of information isolation and analysis deviation in a traditional method are avoided, and the scientificity and the practical application value of the exploration process are enhanced.

The invention discloses a multi-agent collaborative scheduling method and system oriented to science and technology intelligence analysis, and relates to the technical field of science and technology intelligence analysis, and the method comprises the steps that a task issuing layer outputs a standardized task description by executing task demand element analysis; after the intelligent coordinated scheduling layer receives the standardized task description, closed-loop collaborative decision making is carried out, and a task distribution instruction is output; and the professional agent execution layer drives the data acquisition agent group to acquire science and technology information data through a data access adapter of the data resource layer, executes a science and technology information analysis task, outputs a structured processing result, and visually displays the structured processing result to a user through the task release layer. The technical problem that in the prior art, a science and technology information processing system lacks intelligent task allocation, and consequently the information processing efficiency is low is solved, and the technical effects that four-layer architecture closed-loop cooperation of science and technology information analysis tasks and efficient dispatching of specialized intelligent agent groups are achieved, and the task allocation accuracy and the information processing efficiency are improved are achieved.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a multi-modal information analysis and scheme reminding method, device, equipment and medium, which comprises the steps of receiving input data and converting the input data into multi-modal data, executing optical character recognition and image classification recognition to generate a recognition result, and sending the recognition result to a server; a natural language processing model is used for analyzing fuzzy description to generate an analysis result, a knowledge base is inquired, a knowledge graph is combined to generate an association result, the analysis result, the association result and user feature data are fused to generate an execution scheme, the execution scheme is compared with an abnormal list, supervision confirmation is triggered, and a compliance instruction is generated. And personalized reminding contents are generated. The information analysis integrity is improved through multi-modal recognition, natural language processing and the knowledge graph, supervision confirmation and personalized reminding are introduced, and intelligent, compliant and reliable reminding management is achieved.

The invention relates to the technical field of artificial intelligence, in particular to a big data information analysis method and system based on artificial intelligence, and the method comprises the following steps: obtaining a jump segment direction vector, classifying label nodes with consistent directions, splitting a path lacking a mapping relation to form an interruption segment, recognizing a node with continuous directions as a bridge segment entrance, and obtaining a bridge segment direction vector; according to the method, by means of classification according to the node sequence and the channel number in the segment hopping direction, direction aggregation boundary determination and semantic field combination path position interruption recognition, the node sequence structure positioning precision and the paragraph division reasonability are improved, and the focus analysis set is generated by combining the path segments. Bridge segment connection is screened based on direction consistency, path continuation logic, behavior tracks and aggregation numbers are kept in sequence and hierarchy regularization, a behavior aggregation sequence of a semantic chain is constructed, and the continuity of path recognition in a channel aggregation area and the stability of node attribution are enhanced.

The invention relates to a field information analysis method and system based on RAG and a knowledge graph, and belongs to the technical field of artificial intelligence, and the system comprises a multi-source heterogeneous data collection module which is used for collecting field-related original data; the intelligent document processing engine is used for carrying out cleaning and structured processing on the data and extracting entities, relationships and events; the multi-source knowledge graph construction and management module is used for constructing and fusing multi-sub-field knowledge graphs to form a unified knowledge graph; the RAG retrieval enhancement generation dynamic fusion sequencing module is used for receiving user query, performing multi-channel information retrieval by querying a text vector index and a knowledge graph, performing fusion resequencing on a result, and generating an analysis result by utilizing a large language model; and the agent workflow engine is used for decomposing query into subtasks and scheduling professional agents to cooperatively complete analysis and report generation. Deep semantic understanding, intelligent retrieval and automatic analysis of domain information are realized, and the accuracy and efficiency of information processing are improved.

The embodiment of the invention provides a test case sample cutting method, device and system and a storage medium, and relates to the technical field of network security testing. The method comprises the following steps: constructing an industrial control system attack tactical library; wherein the tactical library comprises classified and arranged attack techniques and corresponding security attributes; performing information analysis and semantic analysis on the test case sample to generate structured data of the test case sample and / or function points in the test case sample; and cutting the test case sample according to the security attribute and / or the structured data and / or the function point to obtain a test fragment corresponding to the security attribute and / or the function point. According to the method, classification-based attack techniques and security attributes are cut by constructing a tactical library, key information can be accurately extracted and test intentions can be understood through information analysis and semantic analysis, redundant tests are avoided, cut test fragments can concentrate on specific security attributes or function points, the test coverage range is more accurate, and the test efficiency is improved. And the distributed security test effect is improved.

The invention discloses an intelligent conference recording system, which has the following beneficial effects that the intelligent conference recording system comprises functional modules such as a conference information acquisition module, a data pre-cleaning module, a conference information transcription module, a conference content intelligent analysis module and the like; according to the invention, multi-modal data such as voice, images and texts can be deeply fused through the conference content intelligent analysis module, and structured data and intelligent analysis are provided for users; cross-conference association analysis can be supported, so that a user can be better supported to make a decision; in addition, the voice recognition precision and the handwritten note recognition precision can be effectively improved. Through the above mode, the invention provides the intelligent conference recording system which integrates efficient conference recording, intelligent information analysis and user personalized demand, can fill the blank of the existing conference recording tool, and better improves the overall working efficiency of conference recording.

The invention discloses an intelligent state information analysis system for centralized control station equipment monitoring, and mainly relates to the technical field of power systems and intelligent monitoring. Which comprises an information analysis management module and an event handling management module, and is characterized by further comprising a service tracking management and control module, the information analysis management module is used for carrying out event processing on alarm signals, and the information analysis management module is provided with a power monitoring knowledge base; and the power monitoring knowledge base is used for collecting, sorting, managing and analyzing data and knowledge related to monitoring, and supporting system monitoring, event management, problem diagnosis and decision making. The method has the beneficial effect that the health management level of the power transformation equipment can be effectively improved.

The invention relates to a circuit board on-line defect detection method and system, and the method comprises the steps: carrying out the synchronous collection and structural integration of multi-source technological parameters such as production line environment temperature and humidity, equipment operation states, material batches and the like, and defect detection images, and achieving the construction of large-sample original data in a production process; through standardization and de-noising preprocessing, multi-modal features are fused, and a distribution mapping model of process and defect features is established by using algorithms such as mutual information analysis and principal component analysis. Based on a feature distribution model and real-time data, a dynamic anomaly detection threshold is adaptively generated, Bayesian inference and evidence reasoning are combined, multi-level confidence levels and risk response suggestions are output, and self-learning evolution of the model and the threshold is realized through a closed-loop feedback mechanism. According to the scheme, the accuracy of anomaly detection, the response timeliness and the risk disposal intelligent level are improved, the method adapts to complex working conditions and batch changes, and the closed-loop optimization and safety control capability of the production process is remarkably enhanced.

The invention discloses a building facade three-dimensional surveying and mapping system and method based on an unmanned aerial vehicle and AI, and relates to the technical field of building surveying and mapping, and the system comprises a scene analysis module which is used for executing the information analysis of calibration scene information, and marking each surveying and mapping sub-region as a to-be-collected node; the acquisition planning module is used for calculating the node transition probability of each node to be acquired; the surveying and mapping search module is used for configuring a virtual unmanned aerial vehicle and performing selective iteration of surveying and mapping sub-regions by using pheromone concentration and heuristic factors; the clustering sharing module is used for carrying out three-dimensional surveying and mapping on the exterior facade of the building and establishing a shared information pool in a clustering manner; and the surveying and mapping optimization module is used for carrying out collaborative decision optimization on the local path and updating the acquisition path according to a collaborative decision optimization result. The technical problems of low surveying and mapping efficiency and large measurement error caused by difficulty in meeting large-scale and high-precision surveying and mapping requirements of modern buildings in the prior art are solved, and the technical effect of improving the surveying and mapping efficiency and precision of the buildings is achieved.

The invention discloses a multi-modal data processing method and device based on a large model, equipment and a medium. Performing feature extraction and association mining on the multi-modal data to obtain multi-modal data features; according to a retrieval sequence of the multiple text matching methods, sequentially using the multiple text matching methods to perform text retrieval on the multi-modal data features in a pre-constructed knowledge base to obtain a first associated sub-graph; based on the semantic similarity between the multi-modal data features and multi-modal data in a pre-constructed knowledge base and a similarity threshold value, determining a second associated sub-graph; performing standard evaluation on the plurality of candidate results in the first associated sub-graph and the second associated sub-graph, and sorting the plurality of candidate results according to an evaluation result to obtain a retrieval result; inputting the retrieval result and the multi-modal data features into a large model for information analysis to obtain prompt information and a target tool; and sending the prompt information and the target tool to the terminal, and receiving a data processing result of the terminal.

The invention discloses a test case generation method and system for security and futures software. The method comprises the following steps: converting data in an original file into an embedded vector through an information analysis agent, and storing the embedded vector in a vector database; generating an initial test case set by using the plurality of test points and the data fragments corresponding to each test point through a case generation agent; constructing a business rule atlas to perform rule similarity scoring on each test case, deleting the test cases with low scores, and forming a high-score test case set by the test cases with high scores; semantic similarity scoring is carried out according to the historical test cases, sorting is carried out according to scores from high to low to form an optimal test case set, and the test case with the highest score is marked as the historical test case to be stored in the vector database. According to the method, the test cases of the security futures software can be automatically generated, redundant cases are reduced by evaluating the test cases, the case quality is improved, the workload of testers is greatly reduced, and the test efficiency is greatly improved.

The invention discloses a primary tea grade screening method, a medium and equipment. The method comprises the following steps: acquiring original primary tea information containing a first visible light image, first near infrared spectrum information and first three-dimensional form information according to a preset sampling frequency; performing illumination compensation, geometric correction and multi-source registration processing on the original raw tea information to obtain standard raw tea information; extracting static quality parameters such as strip crimpness from the registered second visible light image, analyzing and acquiring physical and chemical quality parameters from the second near infrared spectrum information, and extracting structural features such as strip compactness from the second three-dimensional form information; finally, grade judgment is conducted through the cascade decision model, and the sorting device is controlled to execute corresponding sorting actions. Fusion analysis and intelligent grading of multi-dimensional features of the raw tea are achieved, and the sorting precision and efficiency are effectively improved.

The invention discloses an intelligent dynamic prediction method for a coal and gas outburst dangerous area of a working face, and the method comprises the steps: building an integrated early warning information analysis platform, dynamically collecting key parameters in a mine, and constructing a dynamic data set; and calculating a coal seam firmness factor and a gas emission factor by utilizing a data fusion technology and combining historical data and regression analysis. Furthermore, in combination with a static data set, such as geological and ventilation system distribution data, a multi-parameter coupling prediction model is constructed. The model is trained and verified through a machine learning method so as to predict the coal and gas outburst risk of the working face in real time. The system automatically triggers early warning according to a model prediction result and a preset threshold value, a scientific basis is provided for coal mine safety management, and coal and gas outburst accidents are effectively prevented.

The invention relates to a contradictory dispute mediation protocol generation method and device based on an artificial intelligence large model. The method comprises the following steps: acquiring original data related to a contradictory dispute event and uploaded by a user; performing data preprocessing on the original data to obtain text data; performing sentiment analysis on the text data based on an artificial intelligence large model to obtain a sentiment analysis result; performing legal retrieval on the text data based on an artificial intelligence large model to obtain a legal retrieval result; generating a protocol draft through an artificial intelligence large model; performing benefit balance review on the protocol draft to obtain an updated protocol; and filling the update protocol into a preset standard template to form a formal adjustment protocol file. According to the invention, a one-stop solution from case information analysis to mediation protocol automatic generation is realized. The system aims at assisting basic-level mediation personnel to perform mediation work more efficiently, and ensures that the generated mediation protocol is fair and reasonable and conforms to legal regulations, so that the success rate and efficiency of mediation are improved.

The invention discloses a personalized intelligent interview system, and relates to the technical field of artificial intelligence and recruitment interview, and the system comprises a position information analysis module which is used for inputting an original position description text, carrying out the analysis through employing a natural language processing NLP technology, and extracting structured position demand data containing skill items, characteristic items and quantification levels; the resume / position intelligent matching module is used for receiving the structured position demand data, receiving a job seeker resume text, performing intelligent matching analysis by constructing a skill semantic vector space, and outputting a multi-dimensional matching score matrix and an investigation key index set; according to the job demand and the job seeker resume, personalized interview topic screening and optimization are realized, and the interview pertinence and accuracy are improved; the job seeker is comprehensively evaluated, and the resume / position matching information is combined, so that a more comprehensive evaluation and scoring basis is provided, and an enterprise is helped to make a more accurate recruitment decision.

The invention relates to an earthquake intensity field disaster situation acquisition system, and discloses an earthquake intensity field disaster situation acquisition system, which comprises the following modules: an unmanned aerial vehicle hardware platform, a disaster situation data acquisition module, an intelligent disaster situation analysis module, a disaster situation prediction and decision support module and a disaster situation return and dynamic response module. The unmanned aerial vehicle carries a high-definition camera, a thermal imager, a laser radar sensor and a meteorological sensor, collects image data, thermal imaging data, three-dimensional point cloud data and meteorological data of a disaster area in real time, and carries out disaster identification and evaluation through a deep convolutional neural network. In combination with multi-sensor data, the system can automatically identify disaster information such as building damage degree, fire areas, casualties and the like, intelligently optimizes resource allocation according to disaster assessment results, and ensures that rescue resources can be timely and accurately allocated to most required places of disaster areas.

The invention relates to the technical field of emergency safety, in particular to a convenient police system and method, and the method comprises the steps: obtaining real-time alarm information provided by a case reporter; analyzing the real-time alarm information according to the first danger feature information to obtain a danger score corresponding to the real-time alarm information; according to the second danger feature information, analyzing the real-time alarm information to obtain a target escape route of the target suspect; and generating a police strategy according to the danger score and the target escape route. According to the method provided by the invention, a basic evaluation-dynamic correction-environment adaptation calculation framework is established, so that the crossing from static evaluation to intelligent early warning is realized, and support is provided for accurate police decision making. Danger scores and target escape routes are obtained through multi-dimensional information analysis, police strategies are graded, resources are accurately matched, leap-type development from passive response to intelligent pre-judgment is achieved, and a new-generation decision support method is provided for modern police service disposal.

The invention relates to the field of artificial intelligence, and discloses a brain-like computing-driven visual information instant analysis method and system, which comprises the following steps of: firstly obtaining real-time perception data and a neural pulse signal, analyzing a signal perception curve to construct a brain-like computing network, then identifying visual information characteristics through the network, analyzing a preset model computing architecture, and obtaining a brain-like computing network; optimizing a neuron mapping relation to obtain an optimized mapping network, analyzing a path based on the analysis information, determining a time sequence distribution state of target data, calculating an analysis efficiency value, determining an analysis optimization direction, generating an instant analysis strategy, calculating an analysis attenuation rate, determining an analysis state according to the attenuation rate, analyzing an analysis dimension, and finally constructing an optimization analysis scheme. According to the invention, the intelligent analysis efficiency of the visual information can be improved.

A method and system for geometrical and topological information analysis for an explainable damage assessment are developed. The system stores pre-disaster and post-disaster point cloud data in computer memory which is connected to a server via a network. The portions of the pre-disaster and post-disaster point cloud data corresponding to the regions of interest are segmented out using geometrical analysis. Features based on topological data analysis techniques for these portions are extracted and stacked as the index reflecting the innate geometrical and topological properties for potential damage assessment. A collection of classifiers are trained to group the damage levels for each region of interest. The damage assessment results identified by the classifiers and a set of explainable items justifying the classification results are reported to a human-readable device.