Core Insights - The announcement highlights a series of management adjustments at Lianjian (Jiangsu) Technology Co., Ltd., including the resignation of founder and former chairman Yang Jiangjin, and the election of Zhou Jianfeng as the new chairman, aligning with the company's strategic focus on high-quality development [1][2] Management Changes - Yang Jiangjin will continue to serve as a director and chief strategic growth officer, focusing on long-term strategic planning and resource integration, ensuring the retention of industry expertise while enhancing management's strategic execution capabilities [2][4] - Zhou Jianfeng, the new chairman, has nearly 25 years of experience in the inspection and testing industry, having held various key positions within the company, which ensures continuity in strategic direction and operational execution [3][4] Governance Upgrade - The management reshuffle is part of a broader effort to optimize governance structures and clarify roles, creating a dual-core framework of "strategy + execution" that enhances both strategic continuity and operational vitality [4] - The inspection and testing industry is undergoing a transformation towards intensification and high-end development, with technological innovation and global expansion being critical competitive factors [4]

Group 1: Company Overview - The company, originally established in 1959, was listed on the Shenzhen Stock Exchange on August 31, 2022, and specializes in inspection and testing certification services [1] - In 2024, the revenue breakdown is projected to be 69.22% from testing services, 15.82% from product sales, and 13.24% from specialized engineering services [1] - The company has received multiple accolades, including being recognized as a "National Advanced Unit in Construction Engineering Quality Testing" and a "Key High-tech Enterprise under the National Torch Program" [1] Group 2: Financial Performance - In 2024, the company reported a revenue of 1.354 billion yuan, a year-on-year decrease of 0.4%, and a net profit attributable to shareholders of 17 million yuan, down 83.59% [2] - For the first three quarters of 2025, the company achieved a revenue of 1.012 billion yuan, a year-on-year increase of 6.23%, and a net profit attributable to shareholders of 35 million yuan, up 67.12% [2] - The company’s cash flow from operating activities in 2024 was 94 million yuan, an increase of 130 million yuan year-on-year, and the asset-liability ratio stood at 28.73%, indicating a low level of debt [2] Group 3: Growth Strategy - The company is pursuing a dual strategy of "internal growth + investment and mergers" to accelerate market penetration and expand into Southeast Asia and the Middle East [2] - In August 2023, the company acquired 55% of Southwest Testing for 80.9 million yuan to expand its foundation and environmental testing business [2] - In October 2023, the company purchased 55% of Guanbiao (Shanghai) Testing Technology Co., Ltd. for 82.5 million yuan to strengthen its automotive testing market presence [2] Group 4: Future Projections - The company aims to achieve net profits attributable to shareholders of 75 million yuan, 120 million yuan, and 180 million yuan for the years 2025, 2026, and 2027, representing year-on-year growth rates of 354.2%, 60.1%, and 50.2% respectively [3] - Corresponding price-to-earnings ratios for these years are projected to be 38.62, 24.13, and 16.07 [3]

证券代码：301115 证券简称：联检科技 公告编号：2025-077 出资额：20,000万元整 本公司及董事会全体成员保证信息披露的内容真实、准确、完整，没有 虚假记载、误导性陈述或重大遗漏。 一、与专业投资机构合作投资的概述 为促进联检（江苏）科技股份有限公司（以下简称"公司"、"联检科技"）长 远发展，充分借助专业投资机构的专业资源在投资领域的广泛布局及资源整合能 力，为实现公司产业链整合及相关业务的投资，公司作为有限合伙人与专业投资 机构无锡国联金投启源私募基金管理有限公司（以下简称"无锡国联金投启源"）、 北京金沙江联合资本创业投资管理有限公司（以下简称"金沙江联合资本"）及其 他有限合伙人盐城东方投资开发集团有限公司、苏州市历史文化名城发展集团创 业投资有限公司、北京中投鼎新投资管理有限公司合作投资设立源测智能科创产 业基金（有限合伙）（暂定名，具体以企业登记机关最终核准登记的名称为准， 以下简称"源测基金"、"合伙企业"、"基金"），并签署合伙协议。基金规模2亿 元人民币，公司拟以自有资金认缴出资3,900万元，出资金额占合伙企业认缴出 资总额的19.5%。 具体内容详见公司于2025年2月1 ...

Quantitative Models and Construction Methods 1. Model Name: GAN_GRU - **Model Construction Idea**: The GAN_GRU model combines Generative Adversarial Networks (GAN) for feature generation and Gated Recurrent Unit (GRU) for time-series feature encoding to construct a stock selection factor[4][13][14] - **Model Construction Process**: 1. **GAN Component**: - The generator (G) learns the real data distribution and generates realistic samples from random noise \( z \) (Gaussian or uniform distribution). The generator's loss function is: $$ L_{G} = -\mathbb{E}_{z\sim P_{z}(z)}[\log(D(G(z)))] $$ where \( D(G(z)) \) represents the discriminator's probability of classifying generated data as real[24][25][26] - The discriminator (D) distinguishes real data from generated data. Its loss function is: $$ L_{D} = -\mathbb{E}_{x\sim P_{data}(x)}[\log D(x)] - \mathbb{E}_{z\sim P_{z}(z)}[\log(1-D(G(z)))] $$ where \( D(x) \) is the probability of real data being classified as real, and \( D(G(z)) \) is the probability of generated data being classified as real[27][29][30] - GAN training alternates between optimizing \( G \) and \( D \) until convergence[30] 2. **GRU Component**: - Two GRU layers (GRU(128, 128)) are used to encode time-series features, followed by a Multi-Layer Perceptron (MLP) with layers (256, 64, 64) to predict returns. The final output \( pRet \) is used as the stock selection factor[22] 3. **Feature Input and Processing**: - Input features include 18 price-volume characteristics (e.g., closing price, turnover, etc.) sampled over the past 400 days, with a shape of \( 40 \times 18 \) (40 days of features)[18][19][37] - Features undergo outlier removal, standardization, and cross-sectional normalization[18] 4. **Training Details**: - Training-validation split: 80%-20% - Semi-annual rolling training (June 30 and December 31 each year) - Hyperparameters: batch size equals the number of stocks, Adam optimizer, learning rate \( 1e-4 \), IC loss function, early stopping (10 rounds), max training rounds (50)[18] 5. **Stock Selection**: - Stocks are filtered to exclude ST stocks and those listed for less than six months[18] - **Model Evaluation**: The GAN_GRU model effectively captures price-volume time-series features and demonstrates strong predictive power for stock returns[4][13][22] --- Model Backtesting Results 1. GAN_GRU Model - **IC Mean**: 0.1119*** (2019-2025)[4][41] - **ICIR (non-annualized)**: 0.89[42] - **Turnover Rate**: 0.83X[42] - **Recent IC**: 0.0331*** (December 2025)[4][41] - **1-Year IC Mean**: 0.0669***[4][41] - **Annualized Return**: 37.40%[42] - **Annualized Volatility**: 23.39%[42] - **IR**: 1.60[42] - **Maximum Drawdown**: 27.29%[42] - **Annualized Excess Return**: 22.42%[4][42] --- Quantitative Factors and Construction Methods 1. Factor Name: GAN_GRU Factor - **Factor Construction Idea**: The GAN_GRU factor is derived from the GAN_GRU model, leveraging GAN for price-volume feature generation and GRU for time-series encoding[4][13][14] - **Factor Construction Process**: - The GAN generator processes raw price-volume time-series features (\( Input\_Shape = 40 \times 18 \)) and outputs transformed features with the same shape (\( Input\_Shape = 40 \times 18 \))[37] - The GRU component encodes these features into a predictive factor for stock selection[22] - The factor undergoes industry and market capitalization neutralization and standardization[22] - **Factor Evaluation**: The GAN_GRU factor demonstrates robust performance across various industries and time periods, with significant IC values and excess returns[4][41] --- Factor Backtesting Results 1. GAN_GRU Factor - **IC Mean**: 0.1119*** (2019-2025)[4][41] - **ICIR (non-annualized)**: 0.89[42] - **Turnover Rate**: 0.83X[42] - **Recent IC**: 0.0331*** (December 2025)[4][41] - **1-Year IC Mean**: 0.0669***[4][41] - **Annualized Return**: 37.40%[42] - **Annualized Volatility**: 23.39%[42] - **IR**: 1.60[42] - **Maximum Drawdown**: 27.29%[42] - **Annualized Excess Return**: 22.42%[4][42] 2. Industry-Specific Performance - **Top 5 Industries by Recent IC (October 2025)**: - Social Services: 0.4243*** - Coal: 0.2643*** - Environmental Protection: 0.2262*** - Retail: 0.1888*** - Steel: 0.1812***[4][41][42] - **Top 5 Industries by 1-Year IC Mean**: - Social Services: 0.1303*** - Steel: 0.1154*** - Non-Bank Financials: 0.1157*** - Retail: 0.1067*** - Building Materials: 0.1017***[4][41][42] 3. Industry-Specific Excess Returns - **Top 5 Industries by December 2025 Excess Returns**: - Banking: 4.30% - Real Estate: 3.51% - Environmental Protection: 2.18% - Retail: 1.76% - Machinery: 1.71%[2][45] - **Top 5 Industries by 1-Year Average Excess Returns**: - Banking: 2.12% - Real Estate: 1.93% - Environmental Protection: 1.50% - Retail: 1.46% - Machinery: 1.23%[2][46]

证券日报网讯 12月26日，联检科技发布公告称，公司2025年12月26日召开2025年第五次临时股东会， 审议通过《关于修订并办理工商变更（备案）登记事项的议案》等多项议案。 （文章来源：证券日报） ...

Core Viewpoint - Lianjian Technology (SZ 301115) announced the convening of its 27th meeting of the fifth board of directors on December 26, 2025, to discuss the election of the company's chairman [1] Company Summary - Lianjian Technology's revenue composition for the year 2024 is as follows: 82.46% from professional technical services, 15.82% from non-metallic mineral products, and 1.71% from software and information technology services [1] - As of the report date, Lianjian Technology has a market capitalization of 2.9 billion yuan [1]

江苏世纪同仁律师事务所 关于联检(江苏)科技股份有限公司 2025 年第五次临时股东会的法律意见书 联检(江苏)科技股份有限公司: 根据《中华人民共和国公司法》(以下简称"《公司法》")《中华人民共 和国证券法》《上市公司股东会规则》等法律、法规和规范性文件以及《公司章 程》的规定,本所受公司委托,指派本所律师出席公司 2025年第五次临时股东 会,并就本次股东会的召集、召开程序、出席会议人员资格、召集人资格、表决 程序以及表决结果的合法有效性等事项出具法律意见。 上述会议通知载明了本次股东会的召开时间、地点、股权登记目、会议召集 人、会议审议事项、出席对象、出席会议登记办法等事项,以及参与网络投票的 1 江 苏世公 为出具本法律意见书,本所律师对本次股东会所涉及的有关事项进行了审查, 审阅了相关会议文件,并对有关问题进行了必要的核查和验证。 本所律师同意将本法律意见书随公司本次股东会决议一并公告,并依法对本 法律意见书承担相应的责任。 本所律师根据相关法律、法规和规范性文件的要求,按照律师行业公认的业 务标准、道德规范和勤勉尽责精神,出具法律意见如下: 一、关于本次股东会的召集、召开程序 1、本次股东会的召 ...

证券代码：301115 证券简称：联检科技 公告编号：2025-075 本公司及董事会全体成员保证信息披露的内容真实、准确、完整，没有 虚假记载、误导性陈述或重大遗漏。 联检（江苏）科技股份有限公司（以下简称 "公司"）第五届董事会第二十 七次会议于2025年12月26日在公司会议室以现场方式召开。本次会议已于当日通 过电话及口头方式向全体董事、高级管理人员发出了紧急会议通知。本次会议由 副董事长周剑峰先生主持，周剑峰先生于本次董事会会议上就紧急通知的原因进 行了说明，会议应参加董事9名，实际出席董事9名，全体高级管理人员列席会议。 本次会议的召集、召开方式和程序符合《公司法》等法律法规及《公司章程》 的有关规定。 经与会董事审议，以记名投票表决方式，通过如下决议 ： （一）审议通过《关于选举公司董事长的议案》 同意选举周剑峰先生为公司第五届董事会董事长，任期自本次董事会审议通过 之日起至第五届董事会任期届满之日止。同时，免去周剑峰先生副董事长职务， 具体内容详见公司同日在巨潮资讯网（www.cninfo.com.cn）披露的相关公告。 表决结果：同意9票，反对0票，弃权0票。 （二）审议通过《关于修订<总经 ...

证券代码：301115 证券简称：联检科技 公告编号：2025-076 联检（江苏）科技股份有限公司 关于公司非独立董事辞任、聘任高级管理人员、选举职工代 表董事、变更董事长及证券事务代表的公告 本公司及董事会全体成员保证信息披露的内容真实、准确、完整，没有 虚假记载、误导性陈述或重大遗漏。 二、职工代表董事选举情况 经公司股东会审议通过，公司不再设置监事会及监事。同时，为了保证公司治 理结构完整，根据《公司法》《公司章程》等相关规定，公司于2025年12月26日召 开第二届第九次职工代表大会，经与会职工代表审议，同意选举朱晔女士（简历详 见附件）为公司第五届董事会职工代表董事，与公司现任董事组成第五届董事会， 任期自本次职工代表大会通过之日起至第五届董事会任期届满之日止。 本次选举完成后，公司董事会成员中兼任公司高级管理人员及由职工代表担任 的董事人数未超过公司董事总数的二分之一，符合相关法律法规的要求。 三、董事长变更情况 公司于近日收到公司董事长杨江金先生的书面辞职报告，为更有利于公司长远 治理结构的优化，并顺应新阶段战略深化与执行的需要，杨江金先生经慎重考虑， 申请辞去公司董事长职务。辞职后，杨江金先 ...

证券代码：301115 证券简称：联检科技 公告编号：2025-074 3.本次股东会采取现场投票、网络投票相结合的方式召开。 1.会议召开时间： （1）现场会议时间：2025年12月26日（星期五）14:30 （2）网络投票时间：通过深圳证券交易所交易系统进行网络投票的具体时 间为：2025年12月26日9:15—9:25，9:30—11:30，13:00—15:00；通过深圳证券 交易所互联网投票系统的具体时间为：2025年12月26日9:15至15:00期间的任意 时间。 本公司及董事会全体成员保证信息披露的内容真实、准确、完整，没有虚 假记载、误导性陈述或重大遗漏。 1.本次股东会未出现否决提案的情况； 2.本次股东会未涉及变更以往股东会已通过的决议的情况； 5.会议主持人：本次会议由副董事长周剑峰先生主持 6.召开情况合法、合规、合章程性说明：本次会议的召集、召开和表决程序 符合有关法律、行政法规、部门规章、规范性文件和公司章程的规定，所作决 议合法有效。 1.出席会议的总体情况 通过现场和网络投票的股东126人，代表股份64,471,835股，占公司有表决权 股份总数（已剔除截至股权登记日公司回购 ...